From the rainforest to the ocean, artificial intelligence is decoding nature’s most complex data patterns and is proving to be a game-changer in conservation.



For as long as there has been wildlife conservation, there has been a need for data. In order to understand ecosystem health, animal behavior and population trends, you have to be able to measure what’s going on in nature. And while there are many ways to do this, from drones to tracking devices, thermal cameras and even rangers on-foot, satellite imagery and camera traps have made study- ing wildlife movement a little bit easier. Not only can conservationists collect ample data, there’s minimal disturbance to animals. When it comes to analyzing the imagery, all that’s really needed is someone who can recognize an animal and there are many training programs to do just that.



But to really understand ecological trends, there are many creatures that are simply too small to be captured through pictures. “With very big animals like elephants, you can see them using satellite data which is great but a significant portion of the ecosystem is hidden,” says Dr Juan Lavista Ferres, who has worked in the field of artificial intelligence (AI) for over 20 years, and is the Chief Data Scientist of Microsoft’s AI for Good Lab. Luckily, those animals that are undetectable in satel- lite imagery make up for their size with sound, which is where acoustic data comes in – and in the case of ani- mal sounds, bioacoustic data. “From a noise perspec- tive, they are there,” laughs Ferres. “There is no corre- lation between the size of an animal and the sound it makes. Very small animals can make a lot of noise and can do very specific frequencies.”



<h1 class="wp-block-heading" id="h-nature-s-silent-signals">Nature’s silent signals</h1>



There’s huge potential in environmental recordings (bio- acoustics are important bioindicators —they are nature’s health signalers) and the good news is that a lot of the data is already available. At the AI for Good Lab, Ferres and his team have continuous surveillance recordings from the Amazon that go back to 1992. The problem is that there are only a handful of scientific experts who can understand what is going on when the data is visualized, and then interpret the frequencies to identify specific animals. “It’s extremely niche. In the case of bioacoustic data, you need a huge level of expertise and there are very few people in the world that can recognize these sounds and frequencies,” adds Ferres.



Another challenge is that going through all of this audio takes time. Ferres says that many of the record- ings he has run non-stop, day and night, for 365 days. “A person would need to be listening to these sounds for a whole year to get through just one year’s worth of data. Now imagine that you have multiple recordings in one forest?” There’s simply too much data for hu- mans to process manually, which is why AI is such a game-changer in conservation – it’s making research a much more efficient process. AI can learn from these experts to automate identifying and classifying animal sounds across large datasets. “We can go through all of the recordings and understand how the health of the ecosystem is changing,” says Ferrers. “Now that we have more compute and better models, we can work with these different types of data, whether it’s images, videos or acoustic data.”



<h1 class="wp-block-heading">Under the sea</h1>



One of the AI for Good Lab’s first projects using acoustic data was with endangered beluga whales in Alaska us- ing underwater sensors. “You can capture the sound of these whales, their vocalizations,” says Ferres. Because sounds travel much further than visual cues, with acous- tic data, researchers can detect (and even potentially identify) different types of whales over vast distances in the ocean, far beyond what would be possible with visual observation methods. “There are particular frequencies in the water that will be very difficult to detect without AI,” adds Ferres. “You can’t solve a problem if you can’t measure it. By doing this, we can actually start measuring the problem.”



Working with different industries and partners throughout the world, Ferres’ hope is that now that the information is in these AI models, more people will be able to use them to track animals over time. All the work that comes out of the AI for Good Lab is also open source which means all of the projects are freely available to re- searchers and organizations worldwide. “It’s a complete philanthropic effort. We give up the idea. We publish everything. All the work we do is for the societal good,” he says. “AI is not just the solution, but sometimes it’s the only solution we have.”

Botswana. Woman photographing giraffe in Chobe National Park with tablet.

Work On The Wild Side: How AI Is Helping Conservation In Africa And The Huge Potential Of Environment Recordings

With The Spurt In Healthtech, AI-powered apps Are Now All The Rage Offering Groundbreaking Interventions In Africa’s Battle against Rising Obesity Rates.



It’s an issue that affects a bulk of the continent’s population.



In Africa, where rising rates of obesity present a growing public health crisis, researchers and innovators are now turning to artificial intelligence (AI)-powered tools to combat the epi- demic. According to the World Health Organization (WHO), in 2022, 2.5 billion adults worldwide were classified as overweight, with over 890 million living with obesity. The problem is becoming especially urgent in low- and middle-income countries. In Africa alone, the number of overweight children under five has increased by nearly 23% since 2000, signaling a dramatic shift in public health needs across the continent.



One of the figures joining the battle against obesity through AI Richmond Essieku, a Ghanaian doctoral student at Texas Tech University. Essieku has reportedly identified 13 genes as potential biomarkers for obesity, with four of them already confirmed. His research is now being translated into a practical solution: an AI- powered mobile app, tentatively titled Generating Artificial Intel- ligence (AI) Based Algorithms to Model and Predict Genotype-by- Socioeconomic Status Interaction for Precision Obesity Detection. This app is designed to model the interaction between genetics and socioeconomic factors in order to provide a more accurate picture of obesity risk in individuals, particularly in Africa, where such nuances are often overlooked.



AI-powered tools like Essieku’s app are not the first examples of how AI can help address the complex factors contributing to obesity. Globally, AI has been used in various ways to combat obesity — from monitoring dietary habits to creating personalized fitness plans. In the United States (U.S.), platforms like Lark Health use AI to offer real-time health coaching, helping users monitor their eating habits and physical activity.



Similarly, Noom, a popular weight-loss app, uses AI to provide personalized advice and insights into user-behavior, which can lead to long-term lifestyle changes.



With the number of smartphone subscriptions in sub-Saharan Africa expected to reach 689 million by 2028, according to Statista, mobile technology offers a promising platform for AI-powered health interventions. AI-driven mobile apps can help individuals monitor their weight, track their food intake, and maintain healthy levels of physical activity. These apps can be tailored to include traditional African foods in dietary rec- ommendations, making them culturally relevant and easier for users to adopt.



The global applications point to the potential for similar systems tailored specifically to African contexts. Abideen Ola- supo, founder of MyAIFactchecker, an AI fact-checking platform based in Nigeria, highlights the importance of culturally-local- ized solutions. “We want to build people’s confidence in explor- ing how they can interact with AI to find safe and effective ways to combat obesity,” Olasupo tells FORBES AFRICA. “For a long time, many have turned to harmful concoctions that negatively impact their health. Africa’s unique challenges cannot be under- stood from the outside, which is why we’ve been researching the solutions people seek online. Obesity, in particular, is a sensitive issue that many feel ashamed to confront.”



MyAIFactChecker is one of several platforms working to ensure that AI solutions are tailored to Africa-specific chal- lenges. Olasupo explains that the platform sifts through different themes, including health and nutrition, to ensure that data is lo- calized and actionable. He notes that combating obesity in Africa requires integrating AI into the daily lives of Africans in ways that are culturally relevant and accessible.



AI’s ability to personalize interventions is especially critical when considering the unique challenges Africa faces in address- ing obesity. Many Africans live in ‘food deserts’ — areas where healthy food is difficult to find or too expensive to buy. Physical activity can also be limited by unsafe environments or long work- ing hours, making traditional approaches to weight-loss difficult to implement.



Africa’s healthcare infrastructure faces significant challeng- es, including a shortage of healthcare professionals and limited access to health facilities. AI is helping to alleviate these issues by offering remote monitoring and telehealth services for obesity management. In countries like Nigeria and Ghana, where access to healthcare is often limited, AI-powered remote health services could provide essential support to individuals looking to manage their weight.



AI-powered health apps are gaining popularity in Africa, also offering personalized recommendations for diet and exercise.



In Nigeria, the startup WellNewMe is using AI to provide us- ers with customized health assessments based on their lifestyle choices. The platform uses machine learning algorithms to ana- lyze users’ eating habits, physical activity, and medical history. It then generates recommendations to improve their health and reduce the risk of obesity-related conditions. For example, users can receive tailored meal plans, exercise routines, and lifestyle tips, all customized to their specific health profiles.



A similar initiative is underway in Ghana, where mPharma, a healthtech company, has developed the mymutti Mobile app. While primarily used to offer affordable medications, the app has recently integrated an AI-powered feature that tracks users’ body mass index (BMI) and offers recommendations for healthier liv- ing. Users receive customized tips on maintaining a balanced diet, increasing physical activity, and managing weight through simple lifestyle changes.



In Rwanda, AI is being used to improve access to healthcare in rural areas where obesity is on the rise. The Babyl Health plat- form, which uses AI to provide remote medical consultations, has been instrumental in helping individuals in rural communities access healthcare services. Through the app, users can consult with doctors about weight-related issues, receive prescriptions, and get referrals to local health facilities for further treatment.



Farming innovations to support the health sector



AI’s role in combating obesity extends beyond healthcare to the agricultural sector, where it is being used to improve the avail- ability of healthy, affordable food. In Nigeria, the startup Zenvus is leveraging AI to help farmers increase crop yields and reduce food waste. By using AI-powered sensors, Zenvus collects data on soil conditions, weather patterns, and crop health. This data helps farmers make informed decisions about when to plant, irri- gate, and harvest their crops, resulting in higher yields and more efficient food production.



Another example is FarmPin, a South African agritech com- pany that uses AI and satellite imagery to monitor crop health and predict food shortages. By analyzing data from farms across the country, FarmPin helps farmers optimize their production and ensure a steady supply of fresh produce to local markets. This, in turn, makes healthy food more accessible and affordable, reducing reliance on processed foods that are often linked to ris- ing obesity rates.



Public health experts are also optimistic about the potential of AI to offer scalable solutions for obesity prevention in Africa. Opeyemi Adam, a public health expert based in Lagos, explains that AI could help overcome some of the challenges of limited healthcare resources in many African countries. “Obesity is often thought of as a personal issue, but it’s deeply systemic,” Adam says. “AI offers a way to analyze large amounts of data and iden- tify trends that would otherwise go unnoticed, which is crucial in places where healthcare resources are stretched thin.”



Adam also points out that many Africans lack access to per- sonalized health advice, something AI could help bridge. “With AI, we could create more personalized health plans that take into account not just the individual’s body weight or fitness level, but also their lifestyle, environment, and even their genetic makeup,” he says.

Scientists Working on Powered Exoskeleton Project in Lab.

Weighing In On The Use Of AI In Helping Combat Obesity

When it comes to controversial advertising campaigns, they usually don’t have to do with income taxes. But a short-lived campaign from enterprise software company Intuit, which makes TurboTax,&nbsp;crossed that line and raised the ire of accountants.



<a href="https://www.forbes.com/sites/kellyphillipserb/2024/10/16/intuit-backpedals-after-insulting-accountants-with-latest-ad-campaign/">Forbes’&nbsp;Kelly Phillips Erb writes</a>&nbsp;about the saga, in which a consumer-targeted message intended to be a bit cheeky and punny&nbsp;ended up insulting a group of professionals who actually rely on Intuit’s products. The centerpiece of the campaign is an advertisement in which a young woman announces to a bland-looking accountant that she’s leaving him for a younger and more fashionable man on her phone “who charges me less but gives me more” as part of a “tax break-up.” The younger man represents Intuit’s “TurboTax Full Service plan,” featuring human tax preparers who work with customers online or in person to complete their taxes.



Tax preparers, who have competed with TurboTax for many years,&nbsp;felt the campaign went too far. The unflattering portrayal of the accountant, plus the barrage of messaging telling consumers to “break up” with them, made many individuals and organizations upset. American Institute of Certified Public Accountants President and CEO Barry Melancon issued a statement saying, “The crucial role of CPAs, who serve as expert and trusted advisors to business owners and individuals, was not reflected in an unfortunate recent ad campaign launched by Intuit.” And the National Association of Tax Professionals said it will no longer accept Intuit’s sponsorships or exhibits at its conference because of the campaign’s “direct conflict with our members’ interests.” Predictably, Intuit decided to phase out the campaign.



While TurboTax is a well-known Intuit product, it’s only one. The company also owns QuickBooks and Mailchimp—financial management and email marketing platforms used by many businesses, including accountants—as well as consumer budgeting tool Credit Karma. In its last fiscal year, the bulk of Intuit’s growth came from those using its enterprise financial planning and email software. TurboTax online made up less than a quarter of the company’s total fiscal year revenues.



Intuit may be seeking more consumer tax business, but it may have damaged its larger customer base by trying to be funny. An average consumer may have giggled at the ad, but it seems unlikely that it would end up getting the desired results,&nbsp;especially since most consumers aren’t thinking about income tax prep in October. Instead, with this campaign, Intuit might have inspired more financial professionals to break up with&nbsp;them.



Finding the right emotional balance is an important tool to make a campaign successful. Reticle AI is using artificial intelligence to determine the emotions that are present in campaigns, helping marketers strike the proper tone to get their messages across. I talked to Vice President of Business Development Tricia Allen about how this works. An excerpt from our conversation is later in this newsletter.



MARKETING MATTERS


<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" width="1024" height="683" src="https://cms.forbesafrica.com/wp-content/uploads/2024/09/GettyImages-2169510342.jpg" alt="" class="wp-image-63122" style="width:608px;height:auto" srcset="https://cms.forbesafrica.com/wp-content/uploads/2024/09/GettyImages-2169510342.jpg 1024w, https://cms.forbesafrica.com/wp-content/uploads/2024/09/GettyImages-2169510342-300x200.jpg 300w, https://cms.forbesafrica.com/wp-content/uploads/2024/09/GettyImages-2169510342-768x512.jpg 768w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /><figcaption class="wp-element-caption"> (Photo by Dilara Irem Sancar/Anadolu via Getty Images)</figcaption></figure></div>


Google is making a change to its Local Services Ads business next month that&nbsp;may impact roughly half of businesses advertising on the search engine,&nbsp;<a href="https://www.forbes.com/sites/brandonkochkodin/2024/10/22/googles-upcoming-ad-change-could-spell-disaster-for-millions-of-unprepared-small-businesses/">reports&nbsp;Forbes’&nbsp;Brandon Kochkodin</a>. Starting November 21, the local ads that pop up at the top of search results for users will be blocked if they aren’t linked to a Google Business Profile. This free profile indicates how businesses appear in search and is fully customizable by the business. But businesses need to be verified as legitimate through video or phone authentication, or by receiving a postcard. The authentication is an extra step, but it’s important that local businesses do it sooner rather than later. Studies have shown that 96% of people learn about local businesses online, and four out of five of those searches convert into business. In fact, nearly half of all Google searches are for local businesses.



SOCIAL MEDIA


<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" width="1024" height="662" src="https://cms.forbesafrica.com/wp-content/uploads/2024/05/GettyImages-1513152452.jpg" alt="" class="wp-image-61892" style="width:632px;height:auto" srcset="https://cms.forbesafrica.com/wp-content/uploads/2024/05/GettyImages-1513152452.jpg 1024w, https://cms.forbesafrica.com/wp-content/uploads/2024/05/GettyImages-1513152452-300x194.jpg 300w, https://cms.forbesafrica.com/wp-content/uploads/2024/05/GettyImages-1513152452-768x497.jpg 768w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /><figcaption class="wp-element-caption"> (Photo by Hakan Nural/Anadolu Agency via Getty Images)</figcaption></figure></div>


Two social networks are making changes that may impact user safety. For as long as X was known as Twitter, users have been able to block other accounts—a step often taken when a user is bothered or harassed by someone. Previously, the blocked account couldn’t see or engage with posts from the user who blocked them. Now, users&nbsp;<a href="https://www.forbes.com/sites/antoniopequenoiv/2024/10/17/x-will-soon-let-users-see-tweets-from-people-who-block-them-the-controversial-change-explained/">can see all posts</a>&nbsp;from accounts that have blocked them, though they still can’t engage with them.&nbsp;X says this change allows “greater transparency,” so users can see if those who have blocked them are trying to “share and hide harmful or private information.” But critics have taken the other side of the argument: Stalkers and harassers can keep following accounts of those who have blocked them. X owner Elon Musk, who has made scores of controversial changes to the platform since he bought it in 2022, previously posted the blocking function made no sense. After this change was made, competing social media platform Bluesky gained 1.2 million users in two days,&nbsp;<a href="https://www.socialmediatoday.com/news/bluesky-gains-momentum-wake-xs-blocking-changes/730371/" rel="noreferrer noopener" target="_blank">Social Media Today reported.</a>



<a href="https://www.forbes.com/sites/lindseychoo/2024/10/17/instagram-sextortion-child-safety/">Changes to Instagram</a>&nbsp;intended to prevent “sextortion” scams and protect teens are much less controversial. Now, users are unable to take screenshots or recordings of disappearing images, which are only intended to be viewed once. The Meta-owned platform is also testing safety notices to let teenagers know when they are exchanging messages with someone out of the country. Images flagged to contain nudity will be automatically blurred for users younger than 18. And accounts with “scammy” behaviors will not be able to see users’ following and followers lists, a common way some bad actors get information about a target’s friends and family.



BRANDS + MESSAGING


<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" width="1024" height="683" src="https://cms.forbesafrica.com/wp-content/uploads/2024/07/GettyImages-1536268798.jpg" alt="" class="wp-image-62351" style="width:556px;height:auto" srcset="https://cms.forbesafrica.com/wp-content/uploads/2024/07/GettyImages-1536268798.jpg 1024w, https://cms.forbesafrica.com/wp-content/uploads/2024/07/GettyImages-1536268798-300x200.jpg 300w, https://cms.forbesafrica.com/wp-content/uploads/2024/07/GettyImages-1536268798-768x512.jpg 768w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /><figcaption class="wp-element-caption">(Photo by Nikos Pekiaridis/NurPhoto via Getty Images)</figcaption></figure></div>


Netflix&nbsp;<a href="https://www.forbes.com/sites/lindseychoo/2024/10/17/netflix-earnings-streaming-beats-expectations-subscriber-growth/">reported earnings</a>&nbsp;last week, beating Wall Street’s expectations. The streaming giant made $9.8 billion in revenue in its most recent quarter, and gained 5.1 million subscribers. Now, nearly 283 million households have Netflix subscriptions, but the rate of new subscriber gain is slowing down.&nbsp;<a href="https://www.forbes.com/sites/dbloom/2024/10/17/netflix-added-51-million-subscribers-can-we-talk-about-what-matters/">Forbes&nbsp;senior contributor David Bloom writes</a>&nbsp;that&nbsp;for Netflix, this really shouldn’t be seen as a negative. After all, there is a finite amount of Netflix subscriptions that can be bought. What is more important, Bloom writes, is viewer engagement. Netflix reported that the average paid membership has two hours of engagement per day. It has an 8.2% viewership share in the U.S., according to Nielsen data. Netflix first became profitable in 2003, and to date only one other streaming service—Disney+—has posted a profit. With more emphasis on engagement, Netflix also seems to be the first of the streamers to start caring more about actual viewers and interaction.



<h4 class="wp-block-heading" id="h-on-message">ON MESSAGE</h4>



<h3 class="wp-block-heading" id="h-how-reticle-ai-uses-technology-to-determine-emotions-in-ads">How Reticle AI Uses Technology To Determine Emotions In Ads</h3>



Emotion is important to marketing. Nostalgia, joy, adventure, curiosity and stress can all inform how consumers make purchases, choose what to eat or drink, or select service providers or leisure activities. Reticle AI uses artificial intelligence to determine the emotions that are present in marketing campaigns, as well as the emotions that consumers are experiencing when they see them, and makes recommendations for an optimal outcome. I talked to Vice President of Business Development Tricia Allen about how their method works and how it can get results. This conversation has been edited for length, clarity and continuity.



How can you use AI to determine things like sentiment and nostalgia?



Allen:&nbsp;We’ve trained our AI technology to understand emotional sentiment within digital content. We’re almost curating content into various emotions. If a brand wants to be associated with nostalgia, [or being] uplifting, joyful, nurturing, they can align their message within content that has that emotional sentiment. We can control how the content potentially makes someone feel. If you’re consuming content that makes you feel nostalgic, nurturing, uplifting, chances are you’re in that frame of mind. If you get served an ad that is in that nostalgic, nurturing tone, you’re more predisposed to take action. That action is that connectivity and attention that the brand is getting because it’s being served at the right time.



[AI has] that ability to take the universe of digital content, really cull it down, and categorize it into these emotional categories because of its understanding of human emotion.



There’s a lot of talk about AI systems not always giving accurate responses. With something difficult to quantify like emotion, how do you make sure that what comes out of your system is accurate to how people actually would feel?



While AI is extremely relevant and helpful from a marketing standpoint, you can’t get rid of that human oversight. I really believe strongly in that for many reasons. There’s bias that’s involved because the technology is only as good as the person who is training the platform, and if they have inherent bias, then the tech has bias. You need more than one person to be vetting that. In addition, what nurturing means to me might mean something completely different to you.



We actually have human labelers. We have them go in and vet our data on an ongoing basis, just to have those human eyes on it. We’ll go through, and if the technology has said this content is deemed to be nurturing, we want to see what a human actually thinks. We have that human component to make sure, because AI is not perfect. Even when it does get better, I still strongly believe you’re going to need human oversight, especially when you’re talking about emotion.



In your research, what are some of the emotions that people are reacting to the most, and what are some more prevalent themes?



A lot of the themes that people are looking for from a marketing standpoint are around joy and that feeling of happiness, and conversely, that feeling of stress and pressure. [It’s] not necessarily a positive emotion. Maybe it’s a negative emotion, because maybe I’m a vacation company and I want to provide you with a solution to help you overcome that stress.



If you are able to tap into emotion—both in marketing and also what is being looked for—what would be the perfect marketing campaign?



To me, the perfect marketing campaign is [one in which] you first do the insights work to understand the emotional footprint of that brand. How do people think and feel about your brand right now? How do you want them to feel about your brand? Then ensure that creative or the ad itself is designed to hit those key emotions. We’re kind-of that end piece. You’ve established how people think and feel. You’ve established: Do I want them to feel this way? If no, where are there distinctions that we can draw on to differentiate from the competition and then make sure that creative is dialed in?



The biggest area where I see brands fall down is they try and tap into emotion, but there’s a disconnect between the creative strategy and the insights work that was done. The insights work is never being brought to life, and then the creative is a bit of a disconnect. When all of those pieces line up, and you take that emotionally designed creative [and] put it in the same environment from a digital placement perspective, that’s the trifecta of emotional marketing.



FACTS + COMMENTS



When the World Series between the Los Angeles Dodgers and New York Yankees begins on Friday,&nbsp;it will be Sho time—for Dodgers star Shohei Ohtani, that is. With the Japanese phenom in the playoffs, Major League Baseball has actually seen&nbsp;<a href="https://www.forbes.com/sites/mattcraig/2024/10/17/ohtani-mania-has-mlb-playoff-viewership-soaring-in-japan/">more October viewership</a>&nbsp;in his home country than in the U.S.



12.9 million:&nbsp;Japanese viewers of NLDS Game 5 on October 11, when the Dodgers beat the San Diego Padres to advance to the National League Championship Series. The U.S. had 7.24 million viewers, a record for a division series



$700 million:&nbsp;Value of Ohtani’s record-setting 10-year contract



‘I hope to continue to perform well as well for the fans in Japan’:&nbsp;Ohtani&nbsp;<a href="https://dodgersnation.com/shohei-ohtani-acknowledges-fans-in-japan-watching-dodgers-postseason/2024/10/21/" rel="noreferrer noopener" target="_blank">told Dodgers Nation</a>, after saying that the team has also been “playing really well”



STRATEGIES + ADVICE



Yes, there is such a thing as too much positivity. Here are some ways to&nbsp;<a href="https://www.forbes.com/sites/jackkelly/2024/10/11/managers-are-glossing-over-workplace-issues-and-pushing-toxic-positivity/">avoid glossing over</a>&nbsp;your employees’ challenges and support your team through hard times.



Time management is difficult for executives. Here are <a href="https://www.forbes.com/sites/jackkelly/2024/10/17/top-time-management-apps/">five apps</a> that can help you get more control over your work day.

Chat Bot Service Concept – Enhancing Customer Experience with Virtual Assistant

Can AI Capture The Emotional Side Of Marketing?

Google’s projections align with a previous study — the Google/IFC e-Conomy Africa 2020 report — which anticipates 167 million new mobile users in sub-Saharan Africa by 2025. This will bring the total number of mobile subscribers in the region to 623 million.



A new report released by Google estimates that artificial intelligence (AI) could contribute over $30 billion to sub-Saharan Africa’s economy in the coming years.



The report, The Digital Opportunity of Sub-Saharan Africa, was conducted independently by Public First, on the region with 70% of its population under the age of 30.



Internet access across sub-Saharan Africa varies significantly, with about 66% of people online in southern Africa, but only 24% in Central Africa, according to Statista. The World Bank reveals that internet usage in West Africa hovers around 30%. The report predicts that even a 1% increase in internet access could lead to nearly a 6% rise in gross domestic product (GDP).



Speaking on the report, Alex Okosi, Managing Director of Google Africa, explains AI’s potential for the region to FORBES AFRICA: “While the report doesn&#8217;t pinpoint specific countries as front-runners in AI-driven growth, it highlights sectors where AI&#8217;s impact is already evident or holds substantial promise&#8230; It emphasizes its [AI] value in the area of automating tasks, boosting efficiency and productivity; and creating new products and services.”



According to the data, 76% of online adults in sub-Saharan Africa identify as entrepreneurs, further highlighting that every dollar invested in digital technologies in Sub-Saharan Africa is projected to generate over $2 in broader economic value by 2030. This finding illustrates the high return on investment (ROI) for digital advancements, particularly in sectors like healthcare, agriculture, and environmental sustainability.



“For the first time, we’ve included an AI curriculum to help business owners understand how they can leverage AI technologies for growth,” Okosi notes. “To further address infrastructure needs, investments like the Equiano subsea cable and our new Cloud region in Johannesburg are critical steps. Additionally, public-private partnerships will play a key role in closing the skills gap by delivering AI training programs and fostering a supportive policy environment that encourages innovation and addresses ethical concerns.”



Entrepreneurs across the continent are already recognizing the potential of AI. Ifeoluwa King, co-founder of VendorStack, a Nigerian social commerce startup, believes AI will touch every sector. “AI will streamline processes, increase efficiency, and cut costs. It will spark innovations from Africa’s creative youths and improve productivity, which will lead to increased revenues,” King tells FORBES AFRICA.

Google

‘AI Curriculum To Help Business Owners’: AI Could Add $30 Billion To Sub-Saharan Africa’s Economy, Report Finds

Navigating the complexities of our future is big business – and big money. Here are some of the more eminent global futurists offering fresh insights into future tech and a better tomorrow.



At the South by Southwest (SXSW) festival in Austin, Texas, there’s one particular session where people start queueing around four in the morning to get a seat. It’s not one of the big-name music performances or a movie screening with awards buzz, it’s a keynote by Amy Webb.



Webb, who is the founder and CEO of the Future Today Institute (FTI), is a futurist. She’s a professor of strategic foresight, a data and research-driven field that unpacks what could be in an increasingly complex world. Webb’s 2024 Tech Trends Report, which is downloaded more than a million times every year, is made up of just under a thou- sand pages of insights businesses rely on to navigate the future.



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
IN HER TALK AT SXSW, AMY WEBB SAID THAT THE NEXT STAGE OF AI IS MERGING DIGITAL SUPERCOMPUTERS WITH HUMAN TISSUE. THIS IS SOMETHING WEBB REFERS TO AS ORGANOID INTELLIGENCE, OR O-AI. SHE PREDICTS THAT BY 2039, O-AI WILL BECOME THE FOREFRONT OF COMPUTATIONAL EVOLUTION, MERGING HUMAN-LIKE DECISION-MAKING CAPABILITIES WITH THE SPEED OF TRADITIONAL COMPUTERS. IN SIMPLE TERMS, WEBB SAYS THAT WE WILL BE ABLE TO MAKE BIOCOMPUTERS OUT OF HUMAN BRAIN CELLS – WE WILL GROW COMPUTERS RATHER THAN BUILD THEM.
</blockquote>



Predicting what comes next may be big business but it’s not necessarily new. While modern futurists use data to forecast pos- sible future scenarios and spot emerging opportunities, the science of probability – long-term planning – has been around since the 1940s. And before futurology became an academic field and job role, science fiction authors like H.G. Wells, Jules Verne and Arthur C. Clarke, were recognized as futurists with an uncanny ability to foresee the world to come. Today, there are a number of well-known futurists sought out by industry giants (and the government) to steer business strategy and adapt to disruptive change. Businesses are hiring futurists to tell them the things they don’t want to hear so that they can prepare for unfore- seen inevitabilities.



Meet the futurists



As the founder of Singularity University and the XPRIZE Foundation, Peter Diamandis is a Silicon Valley digital futurist and engineer who has started over 25 companies. Now in his 60s, Diamandis (whose net worth has been reported to be around $200 million) has many innova- tive projects underway. While tickets to attend his membership-only Abundance Summit begin at $10,000, Diamandis is attempting to change the world with his large-scale XPRIZE competitions that tackle domains like climate, space, biodiversity and deep tech. According to the Key Speakers Bureau, Diamandis’ speaking fee starts at $60,000 – and that’s for a virtual, not in-person, appearance.



As artificial intelligence (AI) becomes more and more popular, there’s a good chance that futurist Ray Kurzweil will be mentioned. Kurzweil, who has received 20 honorary doctorates is a computer scientist and futurist with a 30-year track record of accurate predic- tions – his written predictions, of which there are 147, have an 86% accuracy rate. Kurzweil’s first predictions around AI came out in 1999 and while many people felt that his views were radical when he said that computers would be as intelligent as humans, his estimated date of 2029 doesn’t seem so far off. Kurzweil’s net worth is reportedly around $30 million, most of which comes from the four companies he success- fully founded based on his research and academic prizes. One of his boldest predictions is that immortality will be achievable by 2030 with nanobots – tiny robots that can repair human bodies on a cellular level.



In an interview, he famously said: “By the time we get to the 2040s, we’ll be able to multiply human intelligence a billionfold. That will be a profound change that’s singular in nature. Computers are going to keep getting smaller and smaller. Ultimately, they will go inside our bodies and brains and make us healthier, make us smarter.”



Webb, who has been called ‘one of the five women changing the world’, recently wrote a book called The Genesis Machine with fellow futurist, Andrew Hessel. The book, which won a Gold Axiom Medal, explores synthetic biology, a controversial and emerging techno-science. Biotech, which is something both Webb and Hessel focus on, was a key part of Webb’s 2024 Tech Trends Report. In her talk at SXSW, she said that the next stage of AI is merging digital supercomputers with human tissue. This is something Webb refers to as organoid intelligence, or O-AI. She predicts that by 2039, O-AI will become the forefront of computational evolution, merging human-like decision-making capabilities with the speed of traditional computers. 



In simple terms, Webb says that we will be able to make biocomputers out of human brain cells – we will grow computers rather than build them. Hessel is a pioneer in synthetic biology, microbiologist, geneticist and futurist. He is also the co-founder of a company called Hu-mane Genomics Inc. that engineers synthetic viruses to target cancer cells. “Biology is a very different medium than computing but there are fundamental similarities,” he wrote in a blog post talking about synthetic biology in Af-rica. “Africa is geographically well-positioned to benefit from synthetic biology. Much of the country is in the biological power band of the world, blessed with ample sunlight, fresh water, fertile soils, and incredible biological diversity. But it is also vulnerable to changes in climate, particularly shifts in rainfall and heat waves,” he continues. Hessel has seen first-hand how AI tools are supercharging all aspects of digital biology and predicts that DNA printers are on the cusp of a major upgrade. He believes that in the next five years, we will be able to print and assemble microbial-scale genomes — at reasonable cost and turnaround times.



In the workplace



No matter whether you call them futurists, fu-turologists, foresight practitioners or horizon scanners, it’s becoming increasingly common for organizations to employ professionals with these titles. According to the Univer-sity of Houston, around 25% of Fortune 500 companies have futurists on staff. They’re also commonplace at government agencies as well as non-profits. Andrew Bolwell, for example, is HP’s chief disrupter. In his role, he unpacks megatrends like microfluidics – working with tiny amounts of fluid with precision. Even though printers already do this, Bolwell is talking about even smaller amounts, fluids the fifth of a size of a human cell (or a thousand times smaller than a raindrop). With the microfluidics market projected to be worth $64.94 billion by 2029, according to Mordor Intelligence, the possibility of 3D-printing vital organs may become a reality.



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
&#8220;BY THE TIME WE GET TO THE 2040S, WE’LL BE ABLE TO MULTIPLY HUMAN INTELLIGENCE A BILLIONFOLD. THAT WILL BE A PROFOUND CHANGE THAT’S SINGULAR IN NATURE. COMPUTERS ARE GOING TO KEEP GETTING SMALLER AND SMALLER. ULTIMATELY, THEY WILL GO INSIDE OUR BODIES AND BRAINS AND MAKE US HEALTHIER, MAKE US SMARTER.”&#8211; Ray Kurzweil
</blockquote>



When Dr Werner Vogels, Chief Technology Officer (CTO) and Vice President at Amazon, one of the globe’s most innovative companies, looks into the future, the world takes note.



The well-known futurist, who releases tech predictions for the year and beyond, also happens to be one of the highest-paid CTOs worldwide – it’s no wonder his live speaking fee reportedly starts at $100,000. One of Vo-gels’ predictions is that women’s healthcare, femtech, is on the rise. “Women’s healthcare is not a niche market,” he writes in his tech predictions report. “At AWS, we’ve been work-ing closely with women-led startups and have seen first-hand the growth in femtech. In the last year alone, funding has increased 197%.” 



With increased access to capital, technologies like machine learning, and connected devices designed specifically for women, Vogels believes that the world is at the precipice of an unprecedented shift, not only in the way women’s care is perceived, but how it’s administered. From women in rural areas who have been historically underserved medically to female athletes whose training was modelled on what worked for men, femtech will finally see women’s care move from the fringes to the forefront.



As companies strive to achieve aggressive sustainability targets, there are now climate and environmental futurists emerging as key strategic advisors, guiding businesses in navigating the complexities of climate change, resource management and eco-friendly practices to secure long-term viability and environmental stewardship. For Gerd Leonhard, a German futurist, green has become the new digital and sustainable is the new profitable. In a recent keynote, he said that he’s optimistic about climate change and global warming because we already have the tools we need to solve it. “We’re going to suffer for 15 to 20 years in the process of fixing this,” he predicts, “but we’re now getting ready to do this… technological advancements offer solutions that can help tackle these challenges. It will be essential to find a balance between economic progress and environmental preservation.”



Leonhard, like other consulting futurists, is working with companies to help them understand the next decade and develop foresight. “It’s not predictions, it’s understanding, intuition and imagination,” he explains in a podcast, adding that being a futurist is similar to being a therapist. His job is to essentially point his clients in the right direction; clients who happen to be tech giants, business leaders and government officials around the globe.



The future, today



There’s no question that history is happening now and futurists provide a way to understand current trends as well as anticipate what’s to come. Futurism is essentially risk management because every industry is experiencing dynamic change. In the last 50 years we’ve made more progress than in the previous 250,000 years and it’s been said that the next 10 years will bring more change than the previous 100. Of course, the future is unpredictable and futurists are not fortune tellers – they get things wrong. However, their value lies in their ability to analyze data and identify patterns. By incorporating foresight into strategic planning, businesses, governments and other organizations can adapt more effectively to emerging trends, mitigate risks and seize the moment. In a world characterized by rapid technological advancements, the role of the futurist has become increasingly indispensable in shaping a better tomorrow.

GUI (Graphical User Interface) concept.

The Fortune Of Foresight: Futurists On Tomorrow’s Tech

<h2 class="wp-block-heading" id="h-topline">TOPLINE</h2>



With companies like OpenAI, Google and Meta dropping increasingly sophisticated artificial intelligence products, crowdsourced rankings have emerged as a popular—and virtually only practical—way of determining which tool works best, and LMSYS’s Chatbot Arena has become possibly the most influential real-time gauge.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



While most organizations choose to measure their AI models against a set of general capability benchmarks that cover tasks like solving math problems, programming challenges or answering multiple choice questions across an array of university-level disciplines, there is no industry benchmark or standard practice for assessing large language models (LLMs) like OpenAI’s GPT-4o, Meta’s Llama 3, Google’s Gemini and&nbsp;<a href="https://www.forbes.com/sites/roberthart/2024/06/26/anthropics-claude-what-to-know-about-chatgpt-rival-after-latest-model-trounces-industry-giants/">Anthropic’s Claude</a>.



Even small differences to factors like datasets, prompts and formatting can have a huge impact on how a model performs, and when companies choose their own evaluation criteria, it can make it hard to fairly compare LLMs, Jesse Dodge, a senior scientist at the Allen Institute for AI in Seattle, told Forbes.



The difficulty in comparing LLMs is magnified given how closely leading models score on many commonly used benchmarks, with some companies and tech executives&nbsp;<a href="https://x.com/Ahmad_Al_Dahle/status/1780993216118210899" rel="noreferrer noopener" target="_blank">claiming</a>&nbsp;<a href="https://x.com/AnthropicAI/status/1803790676988920098" rel="noreferrer noopener" target="_blank">victory</a>&nbsp;over rivals with differences as narrow as 0.1%., so close it would likely go unnoticed by everyday users.



Community-built leaderboards deploying human insight have emerged, and in recent years their popularity has exploded in step with the steady boom of new AI tools like ChatGPT, Claude, Gemini and Mistral.



<a href="https://chat.lmsys.org/?leaderboard" rel="noreferrer noopener" target="_blank">The Chatbot Arena</a>, an open source project built by research group&nbsp;<a href="https://lmsys.org/about/" rel="noreferrer noopener" target="_blank">LMSYS</a>&nbsp;and the University of California, Berkeley’s Sky Computing Lab, has proven particularly popular and has built AI leaderboards by asking visitors to compare responses from two anonymous AI models and vote which one is best.



Its scoreboards rank more than 100 AI models based on nearly 1.5 million human votes so far, covering an array of categories including long queries, coding, instruction following, maths, “hard prompts” and a variety of languages including English, French, Chinese, Japanese and Korean.



<h2 class="wp-block-heading" id="h-what-s-the-best-ai-model-on-chatbot-arena">WHAT’S THE BEST AI MODEL ON CHATBOT ARENA?</h2>



The top five AI models on Chatbot Arena’s overall leaderboard are:



<ol class="wp-block-list">
<li>GPT-4o</li>



<li>Claude 3.5 Sonnet</li>



<li>Gemini Advanced</li>



<li>Gemini 1.5 Pro</li>



<li>GPT-4 Turbo</li>
</ol>



<h2 class="wp-block-heading" id="h-what-to-watch-for">WHAT TO WATCH FOR</h2>



Figuring out how to evaluate AI models is set to become increasingly important as more AI tools are rolled out and adopted across society. While benchmarks are important, Vanessa Parli, director of research at Stanford University’s Institute for Human-Centered AI, told Forbes they are also important as “goals for researchers to hit when developing models.” It is important to remember that “not all human capabilities are quantifiable” in a way that we can accurately measure but are nonetheless desirable to have in AI models, Parli said. There is also a clear need for benchmarks to assess traits like “bias, toxicity, truthfulness and other responsibility aspects,” especially for organizations dealing with sensitive information like healthcare companies, Parli said.



<h2 class="wp-block-heading" id="h-crucial-quote">CRUCIAL QUOTE</h2>



“The benchmarks aren’t perfect, but as of right now, that’s the primary mechanism we have to evaluate the models,” Parli told Forbes, cautioning that “researchers can somewhat easily game the system” today, with AI models quickly saturating benchmarks. “I think we need to get creative in the development of new ways to evaluate AI models,” Parli said. “



<h2 class="wp-block-heading" id="h-what-we-don-t-know">WHAT WE DON’T KNOW</h2>



Measuring intelligence is tricky when we do not know what it is we are supposed to be measuring. There is no universally accepted definition of intelligence in humans, let alone a way to measure it, and the possibility, nature and scope of animal intelligence has divided scientists for centuries. While AI benchmarks have typically focused on the ability to perform a particular task, more general assessments will be required in the near future as researchers make progress towards their goal of creating artificial general intelligence (AGI). AGI is capable of excelling and possibly matching humans across a broad set of domains rather than at just one task such as walking, moving boxes, identifying tumors on scans and playing chess.



<h2 class="wp-block-heading" id="h-how-useful-is-chatbot-arena-for-evaluating-ai-models">HOW USEFUL IS CHATBOT ARENA FOR EVALUATING AI MODELS?</h2>



“The rankings [Chatbot Arena] gives are something that I trust more than most other rankings,” Dodge told Forbes, “because it uses a real human to say whether they prefer one generation over another.” Parli suggested assessments like Chatbot Arena could “implicitly evaluate factors” we want in our AI but are less quantifiable than something like coding ability. But she did stress that something like Chatbot Arena should not be the only evaluation method used, saying there are “many factors that should be important to organizations when evaluating models” and it “does not cover all of them.”



.

Einstein And Musk Chatbots Are Driving Millions To Download Character.AI

What AI Is The Best? Chatbot Arena Relies On Millions Of Human Votes

The rapid advancement and implementation of artifi cial intelligence (AI) technologies have signifi cant economic, societal, and ethical consequences for Africa. Efficient governance is crucial to optimizing AI’s advantages while minimizing its risks. This article offers policymakers essential governance issues, suggests strategic methodologies for the appropriate oversight of AI technologies, and presents a framework for AI governance and contextualizes these within the setting of Africa.



Good AI governance must be based on good values. One such value is AI transparency which is essential for AI governance, as it fosters trust, accountability, and fairness. Transparent AI systems allow stakeholders to understand and evaluate decision-making processes, identify and correct biases and assure ethical and legal compliance. The other value is AI truth. Truthful AI prevents misinformation and promotes critical thinking in public conversation, strengthening AI systems’ legitimacy and building social trust needed for widespread adoption and benefi cial integration of AI technology into daily life. The other values are safety and security which are vital for AI systems, as AI interacts with people in different ways, building trust and adoption.



Prioritizing safety reduces accidents and errors in AI-driven industries, safeguarding lives, and money. The other value is ethics. Ethical design and deployment of AI technologies benefit society and minimize harm, including promoting justice, transparency, accountability, and human rights. The other AI value is privacy. Privacy is crucial for AI systems to secure personal data and retain trust in technology. By using strict privacy rules, AI systems protect personal data from unlawful access and exploitation.The AI governance framework proposed in this article entails human behavior, mechanisms for incentives and disincentives, institutional governance structures, policies and regulations, standards, and the law. AI governance involves adhering to AI values, using behavioral science to cultivate a culture that maximizes AI’s potential while minimizing associated risks, and implementing mechanisms to foster a culture that maximizes the potential benefi ts while limiting its associated risks. 



Establishing an institutional structure combining the best practices derived from the Intergovernmental Panel on Climate Change (IPCC) and the International Atomic Energy Agency (IAEA) is recommended to regulate AI effectively. This entity would set global AI standards, monitor compliance, foster international cooperation, address ethical guidelines, establish safety protocols, provide a platform for sharing best practices and promote transparency.Establishing policies and regulations to control AI involves crafting legal frameworks that ensure ethical AI use, focusing on transparency, accountability, and fairness while protecting privacy and preventing discrimination. Key measures could include mandatory AI audits and strict data protection requirements. 



Governments might also create dedicated bodies to oversee AI practices and enforce these regulations, ensuring AI benefi ts society and adheres to ethical standards.Establishing AI standards involves creating uniform guidelines for AI design, development, and deployment, focusing on technical quality, ethical considerations, and compatibility. These standards should cover data privacy, algorithmic transparency, security, and bias prevention. Lawmakers should collaborate with experts and the public to craft adaptable, informed regulations.



This model proposed above governs the following aspects of AI: data, algorithms, computing, and AI applications. Data governance ensures ethical, accurate, and secure use of AI systems, while algorithmic governance ensures ethical behavior and impartial results. Computing governance ensures safe, responsible, ethical, and sustainable AI technology, as computer technologies permeate every part of life. Well-defi ned governance frameworks build public trust, promote more egalitarian technology access, and incentivize good uses of AI. This governance should include specifi c regulations for AI applications in critical sectors like healthcare and fi nance.



AI governance in Africa is crucial to prevent AI from exacerbating existing inequalities that divide the Global South from the Global North and creating new ones. There is a need for robust governance frameworks to ensure that AI systems are used responsibly, minimizing risks, and empowering Africans to benefi t from AI’s potential especially given the fact that much of the AI technology is developed in the Global North. 



Issues such as the potential for AI to displace workers in key sectors in Africa, such as manufacturing and routine service industries, must be dealt with carefully, as AI might eliminate any hope of Africa industrializing. There is also a need to mitigate the negative infl uence of AI on political processes, such as deepfakes and misinformation campaigns. 



African nations must develop national AI strategies, establish independent regulatory bodies, invest in AI education and capacity-building programs, and play an active role in shaping global AI governance discussions through mechanisms such as the African Union and the United Nations. In conclusion, AI governance frameworks must be dynamic and adaptable to technological advancements. Policymakers should collaborate with technologists, businesses, academia, and civil society to create comprehensive governance strategies that ensure AI serves the public good.

AI, Machine learning, robot hand ai artificial intelligence assistance human touching on big data network connection background, Science artificial intelligence technology, innovation and futuristic.

Expert-Speak: An Effective Framework For Governance Of AI In Africa

Artificial intelligence (AI) has made significant strides in all areas of our lives. AI can now monitor patients, safeguard buildings, improve manufacturing processes and write poetry. These are good uses of AI. There are, however, bad uses and characteristics of AI.



For example, AI can discriminate against digital minorities such as people of African descent or ethnic minorities. It can be weaponized with devastating consequences for peace and security. Given that AI is both good and bad, what should be done? We must ensure that AI is used to maximize the good and minimize bad uses. Various strategies have been deployed to maximize the good uses of AI. Furthermore, multiple techniques have been deployed to reduce the bad uses of AI. For example, ensuring that data for training AI systems is representative can minimize algorithmic bias and discrimination.



However, fixing defective algorithms is much easier than improving a flawed human being who intends to use AI negatively. For example, it is far more challenging to change a human being that discriminates against ethnic minorities than to fix an AI machine that discriminates against ethnic minorities. To improve the AI machine, we must apply the best practices of handling data, designing algorithms, and using AI technology, which requires good human behavior.



In AI, discussions of its development, deployment and regulation frequently focus on technological and ethical concerns. However, this discussion’s significant and underexplored aspect parallels human behavior and AI governance. These two generate a complex confluence that considerably impacts how AI technologies are conceived and deployed and how they are regulated. As AI permeates every aspect of our lives, understanding and leveraging this confluence of AI and human behavior is advantageous and is also required for developing AI systems that are both effective and fair. 



Humans are at the heart of AI development, and their decisions, prejudices, and actions affect AI systems.Behavioral science, which studies human behavior   via    psychological, cognitive, and emotional lenses, provides essential insights into how developers and designers should approach the building of AI. It highlights the cognitive biases that can influence algorithm design and the ethical blind spots resulting from prioritizing technical efficiency over social consequences.



Incorporating human behavior into AI governance requires identifying and addressing these human issues. It entails developing frameworks enabling developers to reflect on the potential biases they bring to the design process and cultivating a culture that values ethical considerations and societal wellbeing over technical innovation.



End-user behavior must also be considered when governing AI. Behavioral science provides a lens through which to investigate how people engage with AI systems, such as responding to recommendations, making decisions based on AI-generated data, and building trust in AI technologies. These findings are critical for developing AI systems that are not only user- friendly but also promote beneficial behavioral outcomes, such as improving decision-making processes and preventing the reinforcement of negative biases.



Furthermore, behavioral science can inform public education campaigns on AI, enabling users to be more critical and educated in their interactions with AI systems. Governance frameworks based on behavioral science can raise an understanding of AI’s possible biases and limits, allowing people to interact ethically and effectively with AI.



The link between human behavior and AI governance is dynamic. As AI technologies advance, so will the societal norms and behaviors that shape and are shaped by them. Governance frameworks must be adaptive and ready to respond to new insights from behavioral science into human-AI interaction and the societal repercussions of AI breakthroughs.



This adaptability necessitates a participatory and inclusive governance strategy involving AI developers, users, behavioral scientists, ethicists, policy-makers, and other stakeholders in ongoing discourse. This strategy can help to keep governance frameworks current and thriving in the face of rapid technological development and shifting human behaviors.



Education is critical to guaranteeing the ethical governance of AI since it provides developers and consumers with the knowledge and skills needed to navigate the complicated moral environment of AI technology. Technologists can gain a thorough awareness of the ethical consequences of their work by participating in comprehensive educational programs that integrate ethics, data privacy, and societal effects into the core curriculum of computer science and AI courses. 



Education can help people understand AI technologies, promoting informed and critical engagement with AI systems. By incorporating ethical considerations into all stakeholders’ education in creating and using AI, we can foster a culture of responsibility and accountability. This strategy teaches individuals to foresee and address ethical difficulties and promotes the advancement of AI systems that emphasize human values and social wellbeing. As we set the road for the future of AI, let us not underestimate the value of understanding human behavior in guiding us toward more responsible and beneficial AI governance

AI (Artificial Intelligence) concept. Electronic circuit. Communication network.

The Dynamic Link Between Human Behavior And AI Governance

<h2 class="wp-block-heading" id="h-topline">TOPLINE</h2>



Apple’s new line of&nbsp;<a href="https://www.apple.com/apple-events/" rel="noreferrer noopener" target="_blank">iPad Pros</a>&nbsp;will include a processor the company claims is an “outrageously powerful chip for AI,” as the tech giant laid the groundwork for long-anticipated generative AI features across its products amid&nbsp;<a href="https://www.washingtonpost.com/technology/2024/05/02/apple-sales-ai-iphone-earnings-regulations/" rel="noreferrer noopener" target="_blank">investor concern</a>&nbsp;that it’s falling behind in the race to harness the new technology.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



The new M4 chip represents an upgrade over the M2 chips that powered the last generation of iPads and the M3 chips that power Apple’s current generation of MacBook laptops, the company said in an&nbsp;<a href="https://www.apple.com/apple-events/" rel="noreferrer noopener" target="_blank">announcement</a>&nbsp;Tuesday.



Tuesday’s announcement didn’t offer specifics about potential AI features that could be built into Apple tech, though Tim Millet, Apple’s vice president of platform architecture, gave one example, claiming that users would be able isolate the subject of a 4K video and remove the background with just a tap in Apple’s Final Cut Pro app.



Millet said the neural engine powering the AI capabilities in the M4 chip has been included in Apple chips for years, but this latest neural engine is 60 times more powerful than Apple’s earliest models and “more powerful than any neural processing unit in any AI PC today.”



On Tuesday, Apple announced a new line of&nbsp;<a href="https://www.apple.com/ipad-pro/" rel="noreferrer noopener" target="_blank">iPad Pros</a>&nbsp;that the tech giant called its thinnest yet, coming in 11-inch and 13-inch models with OLED screen technology starting at $999 for the 11-inch model.



It also announced its new&nbsp;<a href="https://www.apple.com/ipad-air/" rel="noreferrer noopener" target="_blank">iPad Air</a>, running on the M2 chip,which comes in a new, larger 13-inch option for $799—both the iPad Air and the iPad pro are available to order online Tuesday and in stores May 15.



Apple&nbsp;<a href="https://finance.yahoo.com/quote/AAPL?.tsrc=fin-srch" rel="noreferrer noopener" target="_blank">stock</a>&nbsp;was slightly up—less than a percentage point—following Tuesday’s announcement.



<h2 class="wp-block-heading" id="h-what-to-watch-for">WHAT TO WATCH FOR</h2>



Apple could unveil more of its plans for AI at its upcoming&nbsp;<a href="https://www.apple.com/newsroom/2024/03/apples-worldwide-developers-conference-returns-june-10-2024/" rel="noreferrer noopener" target="_blank">Worldwide Developers Conference</a>&nbsp;on June 10. CEO Tim Cook said Tuesday the company intends to “talk about the future of our platforms and share some exciting details about what’s to come” at the event. Cook has&nbsp;<a href="https://www.cnbc.com/2024/02/28/apple-annual-shareholder-meeting-2024-ai-investments.html" rel="noreferrer noopener" target="_blank">previously said</a>&nbsp;the company is “investing significantly” in AI and would have more announcements on the subject “later this year.”



<h2 class="wp-block-heading" id="h-contra">CONTRA</h2>



Apple’s plans for artificial intelligence could face immediate competition. The Verge reports Microsoft is&nbsp;<a href="https://www.theverge.com/2024/4/8/24116587/microsoft-macbook-air-surface-arm-qualcomm-snapdragon-x-elite" rel="noreferrer noopener" target="_blank">set to host</a>&nbsp;an event in Seattle this month where it plans to unveil its vision for the future of “AI PCs” and could launch new hardware featuring its Arm AI chips.



<h2 class="wp-block-heading" id="h-key-background">KEY BACKGROUND</h2>



Sales of Apple’s flagship iPhone have been slumping, down 10% year-over-year in the first three months of 2024, driving a 4% decrease in revenue last quarter. And while Apple is considered the most profitable American public company, its stock has been&nbsp;<a href="https://www.forbes.com/sites/dereksaul/2024/05/02/apple-earnings-come-in-hot-as-china-blow-less-painful-than-feared/?sh=5f71ff956903">trending downward</a>&nbsp;of late due to lower iPhone demand in China and concern over Apple’s lack of major plays in the field of artificial intelligence.



<h2 class="wp-block-heading" id="h-big-number">BIG NUMBER</h2>



38 trillion. That’s how many operations the new M4 chip’s neural engine can perform per second, Apple claimed on Tuesday.<a href="https://www.forbes.com/sites/jamesfarrell/"></a>

American multinational technology company Apple store seen

Apple Promises AI Features In New IPad Pro Chips—As AI Tech Race Heats Up

It’s an auditory crisis. The perfect mimicry of the human voice by artificial intelligence (AI) used by criminals to access organizations, discredit governments and leaders, steal data and money, and exploit people and companies. A woman was tricked into thinking her daughter had been kidnapped – the terrified voice on the end of the call was an AI fake. An employee in a multinational enterprise was conned into paying cybercriminals $25 million because he believed he was talking to the company’s Chief Financial Officer and Tom Hanks’ voice was cloned to sell dental plans.



If a fraudster can mimic someone’s voice, they can bypass security checks designed to use voice biometrics. They can fool people into believing that they’re talking to a trusted friend and colleague. They can slide past security barriers and connect with people because their fakes are so good, nobody can tell the difference.



“It’s the trust factor,” explains Adrianus Warmenhoven, cybersecurity expert at NordVPN. “As humans we have implicit trust anchors – I can read your body language when I see you, I can hear inflections and reactions in your voice on the phone and these anchor trust between us. These were developed by being in school, going to work, seeing people. Now they’re being used by criminals to make connections and successful scams.”



Voice is easy to start with. It can be trained easily and there are plenty of applications online. Anyone can download an AI and clone someone’s voice. The technology capable of converting voice to text, text to voice and then applying it to anything from fake bank calls through to scams designed to phish passwords or con family members is readily available.



“How accurately can you pick up someone’s voice? Are the slight tonal differences not just background noise? What if they’ve told you they’re not feeling well? The last two are the highest contributors, accounting for more than 80% of the threats we are seeing in terms of how voice recognition can be compromised,” says Vukosi Sambo, Executive – Head of Data Insights and AIat AfroCentric. 



“We are also seeing instances where someone records a person’s voice and then uses it to authenticate themselves as that person to gain access to information or systems.” 



Getting hold of a person’s voice isn’t difficult either. Cybercriminals simply turn to the one thing they’ve used to hone their craft for years – social media. As Ryan Mer, CEO of eftsure Africa, points out: “People post videos on social media, they share voice notes on WhatsApp, and in the business space, key people have some form of media, whether it’s an interview on TV, radio or a podcast.”



The technology is capable of generating a legitimate voice profile using only a few seconds of these videos and voice snippets. Then, that voice can be used to get in touch with people in the business, especially the finance team, to swindle them out of sensitive information or get them to perform certain tasks. It’s not always a case of getting someone to transfer millions, it can also be trying to access the system for data that can be sold for millions, or to infiltrate a business to commit long-term fraud from within.



Anyone can go onto the dark web and, for a small fee, ask for a deep fake video saying whatever they want. Nobody is going to ask how this will be used. Nobody will care about the repercussions of its use. It is also very likely the next creator of millionaires and billionaires who have used AI to achieve their financial goals, as nefarious as those may be.



Sambo adds: “It’s important to understand what the organization is entitled to in terms of collecting and storing voice data. If you’re not careful, you could infringe individual rights in light of the AI threat. Can companies that record calls for quality and security purposes really protect themselves from this perspective?”



“Considering how this technology is available to anybody these days for next to nothing, security has to take a multi- layered approach,” says Lance Fanaroff, co-founder of iiDENTIFii. “You need to manage access control based on who has access to what; focus on individual access tools such as two-factor authentication and biometrics; and then invest into technologies designed to identify and mitigate potential threats on a granular, individual, level.”



There is a positive side to the conversation – the technologies designed to tackle the threats are evolving just as rapidly. They’re more resilient and alert, capable of adapting to the potential deep fake risks with agility. However, there is only so much a company can do to protect its people and its systems. As Kabelo Makwane, Managing Executive: Cloud, Hosting &amp; Security at Vodacom Business Africa, concludes: “What has become important now is finding the right balance between leveraging the technology, not locking down systems, and still finding a way of layering security so there remains space for growth and productivity.”

Asian woman using smartphone surrounded by beams of light. Metaverse and Artificial Intelligence

AI Has Stolen Your Voice… And Why It’s An Auditory Crisis

Five years ago, I couldn’t imagine asking boards and business leaders whether robots would one day run their companies.



However, the massive increase in awareness of the potential of large language models is forcing executives to explore how to use robots and artificial intelligence in day-to-day decision-making.



In fact, the rise of executive robots has already started.



For example, in May 2023, Forbes reported that Dictador, a progressive premium brand rum distiller, had appointed an AI CEO called Mika.



It is gimmicky for sure, as humans are still very much controlling her AI strings, but as Mika reportedly said in an interview with Reuters, “My decision-making process relies on extensive data analysis and aligning with the company’s strategic objectives.” She went on to explain how she was devoid of personal bias, which helps ensure that strategic choices are prioritized in line with the organization’s best interests, not hers.



This sounds amazing. So, is Mika the forerunner of the mass adoption of AI for corporate governance and leadership roles?



For once, the likely answer is yes, absolutely.



For starters, the demand for a solution like this is apparent.



Humans regularly make bad decisions, and more often than not, this leads to someone losing a lot of money.



Why, for example, did OpenAI’s board sack Sam Altmann (before he returned as CEO in November last year)?



What led Elon Musk to rebrand Twitter to X?



And why didn’t Silicon Valley Bank diversify its risk away from startups?



Decisions like these wipe out trillions of dollars of value every single year. And these three examples are just the tip of the iceberg.



Further, those impacted aren’t just the super-wealthy. Often, it’s the poorest who see their life savings and pensions hit hardest.



All of which means there is a huge interest from everyone, from governments to investors, to find ways to improve decision- making and corporate governance.



We already spend billions of dollars for consultants and business schools to develop leaders and models to help companies maximize profits while minimizing risks.



But these billions will quickly switch to AI alternatives if there is even the smallest of probabilities that technology will help improve a stock’s potential returns.



So, the demand is there.



But how long will we have to wait for the likes of the already hugely-impressive ChatGPT to offer intelligence that can not only answer questions in narrow fields but actually analyze data from multiple sources, draw inferences, consider interdependencies, develop execution plans, draw up funding requirements, consider resource allocations, raise funding and build support along with all the other tasks and activities that are required in any modern-day business?



Mustafa Suleyman, founder of DeepMind and Inflection.AI, explores this question in his recent bestseller, The Coming Wave.



Specifically, he asks how long it will be before machines answer and act on prompts such as “Please design and execute a strategy that will allow me to make $1mill on Amazon in as few months as possible with just $100K of investment.”



His conclusion? “Aside from the legal requirements of registering as a business on the marketplace and getting a bank account, all of this seems to me eminently doable. I think it will be done within the next year and probably fully autonomously within three to five.”



When an industry insider as respected as Suleyman makes a comment like this, we should sit up and listen.



And it makes absolute sense when you consider that a potent combination of factors is driving development in AI. Breakthroughs in machine learning algorithms, dramatic increases in computing power, the abundance of extensive data sets, advancements in cloud computing, enhanced global connectivity, escalating demand across industries and the democratization of access through open-source initiatives are just some of the factors propelling it at exponential rates.



And, of course, the biggest factor of all is perhaps the simple fact that we are now using AI to build AI, as more and more code is being written by machines, not developers. So perhaps the real question isn’t whether or even when robots will run companies. Shareholders and boards might do better considering what types of leaders they need to employ to manage the transition from human to augmented to algorithmic leadership. This is not an easy question to answer. There is no template for designing leadership systems for robots. Perhaps ChatGPT has the answer?

Robot working at desk, 3D Rendering

Expert-Speak: Will Robots Run Companies?

As language models like ChatGPT and Gemini have ushered in a new age of AI in Silicon Valley, the world’s most powerful tech companies are looking ahead to drug discovery and digital biology.



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As Nvidia CEO Jensen Huang scanned the audience at the JPMorgan Healthcare Conference this January in San Francisco, the biggest health tech event of the year, he acknowledged that he was on unusual ground.



“You’re not my normal crowd,” he said to the room of health and biology technologists, during a fireside chat with Recursion, a drug discovery firm that Nvidia pumped $50 million into last year.



The audience may not have been part of his core demographic, but he&#8217;s hoping that will change. Over and over again, Huang has touted digital biology as the “next amazing revolution” in technology. As the AI boom has swept Silicon Valley, Nvidia has built a more than $60 billion a year business and last summer became one of the few companies with a market cap in the trillions. In health and biotech, it sees more opportunities to fuel its growth.



“It&#8217;s been declared we are the next many-billion dollar business for Nvidia,” Kimberly Powell, Nvidia’s vice president of healthcare, told&nbsp;Forbes. She said the company aims to provide chips, cloud infrastructure and other tools to more biotech firms.



Now that large language models like OpenAI’s ChatGPT and Google DeepMind’s Gemini have mainstreamed generative AI, several of the world’s most powerful tech companies are looking to biotech as the next frontier in artificial intelligence — a frontier where AI isn’t generating funny poems from a prompt, but rather the next life-saving drug.



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“It&#8217;s been declared we are the next many-billion dollar business for Nvidia.”Kimberly Powell, Nvidia’s vice president of healthcare
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At Nvidia, arguably a backbone of the AI revolution because of its powerful GPU chips, the bulk of investments at the company’s venture capital arm over the past two years have been in drug discovery. At DeepMind, the Google AI lab’s AlphaFold model — a groundbreaking tool for predicting protein structures — has been used by academic researchers over the past year to develop a &#8220;molecular&#8221; syringe to inject medicine directly into cells, and to research crops that are less dependent on pesticides. The interest in biotech is industry-wide: Microsoft, Amazon and even Salesforce have protein design projects as well.



While using AI in drug discovery is not exactly a new trend — DeepMind first unveiled AlphaFold in 2018 — executives at both DeepMind and Nvidia told&nbsp;Forbes&nbsp;that this is a breakthrough moment, thanks to a confluence of three things: the mass of training data now available, the explosion of computing resources and advancements in AI algorithms. “The three ingredients are here for the very first time,” Powell said. “This was not possible five years ago.”



AI has great potential in the biotech space because of its sheer complexity — just take the problem that AlphaFold targets. Proteins are the basic machinery of your body, managing a wide variety of functions. All of these functions are reliant on the three dimensional shape of a protein. Every protein is made up of a sequence of amino acids, and interactions between those amino acids and the external environment determine how the protein “folds” — which dictates its ultimate shape. Being able to predict the shape of a protein based on its amino acid sequences is of intense interest to biotech companies, which can use those insights to design everything from new drugs to improved crops to biodegradable plastics.



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“It was always this kind of lunatic, fringe thing. Very much out of the mainstream.”David Baker, director of the Institute for Protein Design at the University of Washington
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This is where deep learning comes in: training AI models on hundreds of millions of different protein sequences and their underlying structures help those models uncover patterns in biology without necessarily needing to do the expensive computations required by a true molecular dynamics simulation. Fully simulating proteins requires such intense computational resources that institutions have designed and built supercomputers specifically to handle this type of problem, such as the Anton 2 at the Pittsburgh Supercomputing Center.



The boom in drug discovery tech isn’t only coming from the AI tech giants. Since 2021, there have been 281 venture capital deals worldwide in AI drug discovery startups, accounting for $7.7 billion in investment, according to Pitchbook. The biggest spike occurred in 2021 as the pandemic took hold, when 105 deals were made, up from 65 the year before, tapering to 67 deals in 2023. In a&nbsp;<a href="https://pitchbook.com/news/reports/q4-2023-biopharma-report" rel="noreferrer noopener" target="_blank">report</a>&nbsp;published earlier this month, the analyst firm noted that there’s still a strong level of enthusiasm “for early-stage firms integrating AI into drug discovery and development.” The rise of generative AI has also sparked increased interest, said David Baker, director of the Institute for Protein Design at the University of Washington.



“It was always this kind of lunatic, fringe thing. Very much out of the mainstream,” said Baker. Now, he said, “everyone is talking about it.” Since the Institute of Protein Design’s founding in 2012, more than 20 startups have been spun out of the program, said Baker. Ten of them — including Archon Biosciences, which develops nanomaterials for regenerative medicine and cancer, and Lila, creating treatments for fibrotic diseases — have come in recent years, since 2021.



At DeepMind, it wasn&#8217;t until the Covid-19 pandemic hit that researchers truly understood the stakes of their research. They&#8217;d worked for almost 5 years to develop AlphaFold, and as they were retraining the model for its second generation, the entire world began sheltering in place because of a mysterious virus. “That really brought home the importance of the problem,” Pushmeet Kohli, vice president of science for DeepMind, told&nbsp;Forbes.



The result of DeepMind’s retraining was AlphaFold 2, a groundbreaking model that could so accurately predict protein structures that organizers at CASP, a worldwide research contest for protein folding, emailed DeepMind to ask if the company somehow cheated, Kohli recalled, laughing.



The effort has been so promising that cofounder Demis Hassabis spun out a separate company at Alphabet based on AlphaFold’s breakthroughs in 2021. Called Isomorphic Labs, the startup focuses on drug discovery and is helmed by Hassabis himself. Just this year, for example, Isomorphic Labs inked research deals with&nbsp;<a href="https://storage.googleapis.com/isomorphiclabs-website-public-artifacts/ISOMORPHIC_LABS_LILLY_07_01_24.pdf" rel="noreferrer noopener" target="_blank">Lilly</a>&nbsp;and&nbsp;<a href="https://storage.googleapis.com/isomorphiclabs-website-public-artifacts/ISOMORPHIC_LABS_NOVARTIS_07_01_24.pdf" rel="noreferrer noopener" target="_blank">Novartis</a>&nbsp;collectively worth up to nearly $3 billion if all the milestones are met — and that doesn’t count lucrative royalties from potential drug sales that result from these partnerships.



In 2022, Nvidia unveiled BioNeMo, a generative AI platform that helps developers accelerate the training, deployment and scaling of large language models for drug discovery. At&nbsp;<a href="https://www.forbes.com/sites/richardnieva/2024/02/15/nvidia-nventures-ai-investments/?sh=561e51446025">Nventures, the chip maker’s venture capital arm</a>, seven of the unit’s 19 overall deals have been in AI drug discovery startups, including Genesis Therapeutics, Terray and Generate Biomedicines — the largest of any investment category.



“The computer-aided design industry created the first $2 trillion chip company,” Powell said, referring to Nvidia and its stratospheric rise over the past year. “Why wouldn&#8217;t the same computer-aided&nbsp;drug discovery&nbsp;industry build the next trillion dollar drug company?” She added, “Which is why we are investing in the way that we are.”



Several other tech giants have their own protein folding efforts. Last year, Salesforce debuted ProGen, a protein-generating AI model, and Microsoft released EvoDiff, a similar, but open source model. Amazon also released protein folding tools for SageMaker, its AWS machine learning platform. Even ByteDance, TikTok’s parent company, appears to be recruiting for science and drug design teams,&nbsp;Forbes&nbsp;<a href="https://www.forbes.com/sites/alexandralevine/2024/01/02/tiktok-bytedance-pharmaceuticals-drug-discovery-science-biology-chemistry-ai-china/?sh=3b8b0b250874">reported</a>&nbsp;in January.



Still, as promising and hyped as AI drug discovery is, there are setbacks. It still takes years to get drugs through clinical trials, and while the FDA so far has okayed clinical trials for&nbsp;<a href="https://www.fda.gov/science-research/science-and-research-special-topics/artificial-intelligence-and-machine-learning-aiml-drug-development" rel="noreferrer noopener" target="_blank">over 100 new drug candidates</a>&nbsp;that use AI or machine learning for development, it it will likely be years before any hit the market.



In some cases, the difficulties associated with drug discovery has caused big tech companies to abandon that research. Last August, Facebook parent Meta shuttered its protein folding team. The researchers at the unit later struck out on their own, founding a company called EvolutionaryScale,&nbsp;Forbes&nbsp;<a href="https://www.forbes.com/sites/kenrickcai/2023/08/25/evolutionaryscale-ai-biotech-startup-meta-researchers-funding/?sh=191e6c7e140c">reported last year</a>. Meta declined to comment on the reason for shutting down the project.



One important bottleneck that tech companies will need to focus on is having enough training data. Newer foundational models like GPT are reliant on reinforcement learning, a method where algorithms can process unlabeled information through trial and error. That makes them even more reliant on high-quality data, Anna Marie Wagner, head of AI for synthetic biology company Ginkgo Bioworks told&nbsp;Forbes. Last summer, her company&nbsp;<a href="https://investors.ginkgobioworks.com/news/news-details/2023/Ginkgo-Bioworks-and-Google-Cloud-Partner-to-Build-Next-Generation-AI-Platform-for-Biological-Engineering-and-Biosecurity/default.aspx" rel="noreferrer noopener" target="_blank">entered into</a>&nbsp;a five-year strategic partnership with Google Cloud to pair its AI expertise with Ginkgo’s ability to quickly generate biological data in its automated labs, which can then be immediately put back into the AI model as new training data. This combination, she said, helps to better optimize the discovery process.



Additionally, she said, Ginkgo has the ability to validate model predictions quickly. Counterintuitively, that makes the quirk of AI models sometimes hallucinating — producing wrong or misleading results to a prompt — “a feature, not a bug” because it can lead to interesting discoveries that might have been unimaginable to scientists. “We want the model to come up with the crazy stuff, because that’s where we start seeing order of magnitude improvements.”



Kohli puts the data problem more bluntly: “Garbage in, garbage out.” Still, as the industry works to fix those issues, he has already seen the impact that AI has had on biological research. &#8220;When I go to conferences and see the change in how biologists were doing their work earlier, and how they&#8217;re doing their work today, that&#8217;s an amazing transformation,” he said.

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Why Nvidia, Google And Microsoft Are Betting Billions On Biotech’s AI Future

Artificial intelligence (AI) has emerged as a revolutionary tool, reshaping industries, streamlining processes, and improving decision-making. The success of AI is because we now have access to more data, and we possess adequate computational infrastructure to analyze such data. AI has enormous potential in the legal field, promising to transform how legal practitioners function and individuals access the justice system. 



However, this potential is not devoid of ethical concerns and obstacles.



The function of AI in the legal domain is diverse. AIdriven research tools can rapidly analyze extensive legal databases, furnishing attorneys with insights in a previously unattainable manner. It entails the utilization of chatbots and virtual assistants to provide individuals with legal guidance, thereby enhancing the accessibility of legal information. 



AI saves time and money when producing legal documents using document automation tools.



Predictive analytics can predict legal outcomes, enabling litigants and attorneys to make well-informed decisions. Online dispute resolution platforms provide a viable substitute for conventional litigation, enhancing the efficiency and accessibility of dispute resolution. Nevertheless, as AI gains prominence in law, we must exercise caution and remain vigilant regarding the obstacles to this revolutionary technology.



The first such obstacle is the fairness and bias of AI systems, which are potential sources of concern. Algorithms for machine learning are trained using historical data, which may contain societal biases. AI could perpetuate and even exacerbate preexisting discrimination in the legal system if these prejudices are not addressed. AI development must prioritize fairness and equity, necessitating ongoing vigilance to identify and address bias in AI applications. Secondly, the opaqueness of AI decisionmaking processes raises concerns regarding transparency and accountability. In legal contexts, individuals have a right to be informed of the reasoning behind decisions made by AI systems.



Legal experts and technologists must collaborate to guarantee the transparency of AI systems and allow individuals to contest AI-generated outcomes. However, AI technology is lagging, and AI systems are subjected to the accuracy-transparency dilemma, whereby the more accurate the AI model, the less transparent it is, and vice versa. This is because the high accuracy of the AI model correlates to the increased complexity of the model. Furthermore, the more complex the AI model, the more accurate it is, but this results in reduced transparency of the model.



Thirdly, there is the problem of the security and privacy of individuals. Legal issues frequently necessitate the use of confidential personal data. Implementing robust data protection measures to secure individuals’ rights and privacy is critical.



Legal professionals must thoroughly contemplate the ethical and legal ramifications and enforce rigorous data security protocols when dealing with personal data. This requires technology, which is not necessarily available in many African countries. The African Union (AU) must ensure that groups of countries jointly procure such technologies to reduce the burden of the cost of this technology.



Furthermore, we must train enough people to deploy such technologies. Fourth, as AI’s capacity for legal research and document automation expands, concerns may arise regarding the potential displacement of legal professionals. However, rather than replacing legal professionals, AI should be considered a supplement to their work. By utilizing AI, legal professionals can increase productivity, decrease expenses, and improve their capacity to render expert opinions.



Fifth, legislative bodies and governments must establish transparent regulatory frameworks for AI. These regulations must delineate principles of ethics, foster transparency mandates, and stipulate the responsibility of these AI systems. Achieving an optimal equilibrium between fostering innovation and safeguarding the rights of individuals is a highly challenging endeavor and requires the training of regulators and lawmakers to understand these technologies. 



The AU can be a catalyst to ensure such knowledge is accessible across Africa.



Sixth, a potential benefit of AI in law is its capacity to improve the accessibility of justice. Tools propelled by AI can increase the accessibility of legal information for those who cannot afford legal representation.



Online dispute resolution has the potential to offer economically viable substitutes for conventional litigation. However, we must ensure that these technologies do not exacerbate but rectify existing disparities in access to justice.



AI is not a silver bullet that can solve all legal problems, nor is it the precursor that will end the legal profession as we know it. However, when utilized responsibly and ethically, AI is a tool that has the potential to enhance the agency of legal practitioners and facilitate improved access to justice.



The coexistence of AI and the law can produce a legal system that is more equitable, efficient, and accessible.

AI And The Law –Navigating The Future Together

Finance is a crucial change agent in society, government, and technology.



The introduction of artificial intelligence (AI) is fundamentally altering the financial world. AI is a form of technology that confers intelligence on machines. In my 2013 book, Economic Modeling Using Artificial Intelligence Methods, I demonstrated how



AI could forecast economic indicators, predict stock prices in stock exchanges, perform credit scoring in banks, and model complex financial instruments such as options, futures, and derivatives. In our 2017 book, Artificial Intelligence and Economic Theory, Evan Hurwitz and I demonstrate how AI affects how economists think about demand and supply, pricing, and behavioral economics. Utilizing AI’s capabilities, the financial sector is on the verge of massive disruptive changes that present new opportunities and risks. This article examines how AI affects economic systems, specifically the financial sector, markets, and the government.



Using machine learning, predictive analytics, and natural language processing, AI has the potential to revolutionize the way institutions operate. Additionally, AI opens up new avenues for customer service, risk management, and business advice.



For example, AI-powered chatbots and virtual helpers help with customer service around the clock, simplifying user interfaces and making it easier to answer questions quickly.



Consequently, they enhance consumer experience and reduce expenses. For instance, in risk management and credit scoring, AI algorithms can examine enormous amounts of data to identify patterns and assess risk levels. This makes financial services available to a larger population.



In the investment world, robo-advisors have become popular. They use AI’s analytical capabilities to offer cheap, personalized financial advice. Through these changes, AI is making it easier for more people to use financial services and driving the global financial system to be more open to more people.



AI is also changing the way financial markets work. For example, AI has changed how stocks are bought and sold with high-frequency algorithmic trading. AI can analyze vast financial data in milliseconds to identify trends and make trades. This is a substantial improvement over traditional methods making markets move faster, more open and work better. However, increased market speed ushers market stability and systemic risks, requiring protection and strong oversight to avoid these problems.



Regulators worldwide seek to deal with AI’s problems, such as data protection and algorithmic transparency. Accordingly, there should be a balance between encouraging innovation and protecting the financial security and consumer interests in regulations. AI can simplify compliance procedures, monitor



financial transactions in real-time for illicit activities, and predict market glitches, making regulators more proactive.



In the African market, the African Continental Free Trade Area (AfCFTA), a trade deal that aims to increase trade significantly within Africa, offers unique opportunities for AI.



The agreement covers a broad range of aspects of Africa’s economy, such as digital trade and the protection of investments. Moreover, the number of countries in the AfCFTA will make it the largest free trade area globally, linking 1.3 billion people in 54 countries with a combined GDP of $3.4 trillion. AI can make the AfCFTA work better and reach its goals.



For example, AI can help improve trade logistics by making delivery systems, customs processes, and tracking and tracing more efficient. It can find the best ways to move goods, predict delays, and give traders real-time information. In addition, AI can analyze trade data to identify patterns, trends, and connections. This can help policymakers make better choices and predict and respond to future trends better.



AI-powered systems can make cross-border e-commerce more efficient, a sector expected to grow under the AfCFTA. AI can create personalized product recommendations and automate customer service. In education and training, AI can help people acquire the skills they need for an African economy that works better together.



However, for AI to achieve the goals of the AfCFTA, it is essential to have good AI governance and regulation. Furthermore, we need to invest in digital infrastructure and education.



In conclusion, AI is vital to changing how the world’s economic system works. It affects financial services, markets, and regulation. AI is ushering in a new age of innovation and efficiency.



However, as AI continues to change how the financial world works, a cautious and thorough approach is needed to make the most of its prospects and manage its risks well. There needs to be strong regulatory frameworks, investments in AI literacy and skills, and a commitment to ethical AI values. These objectives are essential if we want an AI-driven financial future that is both prosperous and sustainable in Africa.

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How Artificial Intelligence Affects The Financial Sector In Africa

<h2 class="wp-block-heading" id="h-topline">TOPLINE</h2>



OpenAI—the company behind ChatGPT—is exploring ways for its popular generative artificial intelligence platform to be used in schools, according to <a href="https://www.reuters.com/technology/openai-explores-how-get-chatgpt-into-classrooms-2023-11-16/" target="_blank" rel="noreferrer noopener">Reuters</a>, marking a new undertaking for the company that’s been criticized by some educators for enabling cheating.



<h2 class="wp-block-heading" id="h-key-facts">KEY FACTS</h2>



Brad Lightcap, chief operating officer for OpenAI, said at a San Francisco conference last week that the company will likely create a team next year that will solely look into ways artificial intelligence can be used in education, Reuters reported.



Lightcap said at the conference that “most teachers are trying to figure out ways to incorporate (ChatGPT)” into how they teach, and that OpenAI is “trying to help them think through the problem.”



Artificial intelligence—and ChatGPT, specifically—have been criticized in the past for making it easier for students to cheat, even being&nbsp;<a href="https://www.forbes.com/sites/ariannajohnson/2023/01/18/chatgpt-in-schools-heres-where-its-banned-and-how-it-could-potentially-help-students/?sh=ffd34456e2c6">banned</a>&nbsp;by some schools and districts earlier this year.



<h2 class="wp-block-heading" id="h-big-number">BIG NUMBER</h2>



85%. That’s how many students—out of those who were able to compare human tutoring to using AI—said ChatGPT was more effective than working with a real person,&nbsp;<a href="https://www.govtech.com/education/k-12/is-chatgpt-better-than-a-human-tutor-survey-says-yes" target="_blank" rel="noreferrer noopener">according</a>&nbsp;to Government Technology.



<h2 class="wp-block-heading" id="h-key-background">KEY BACKGROUND</h2>



ChatGPT was released mid-school year last November, and districts nationwide almost immediately began banning the generative AI platform out of cheating concerns. Students are able to use generative AI platforms to write essays and complete homework, though it wasn’t hard to catch, <a href="https://www.nytimes.com/2023/06/30/technology/ai-chatbot-study-aid.html" target="_blank" rel="noreferrer noopener">according</a> to the New York Times, because of AI being in early stages and still “hallucinating,” or making things up. On Dec. 12, 2022, the nation’s second-largest district, Los Angeles Unified School District, became one of the first to block the site to “protect academic honesty,” though at the start of a new school year it introduced its own education-specific AI bot called “Ed” in about 100 schools, Politico <a href="https://www.politico.com/news/2023/08/23/chatgpt-ai-chatbots-in-classrooms-00111662" target="_blank" rel="noreferrer noopener">reported</a>. Other districts that banned it or limited access to the site <a href="https://www.forbes.com/sites/ariannajohnson/2023/01/18/chatgpt-in-schools-heres-where-its-banned-and-how-it-could-potentially-help-students/?sh=ffd34456e2c6">included</a> New York City Public Schools and schools in Montgomery County, Alabama. Since the release of ChatGPT, though, OpenAI has worked to show its value in education. In the fall, OpenAI and nonprofit Khan Academy <a href="https://openai.com/customer-stories/khan-academy" target="_blank" rel="noreferrer noopener">announced</a> a partnership to create an “AI-powered assistant” available to Khan students that works as “both a virtual tutor for students and a classroom assistant for teachers.”

Tag: artificial intelligence

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