How AI Will Shape Society Over the Next 20 Years

What Are Children Learning About AI In School?

As we look to the future, a key question is what children are learning about AI in school. With AI advancing at a rapid pace, it’s crucial to ensure that the next generation is equipped with the knowledge and skills to navigate this rapidly changing landscape.

Rames Sarkar, a colleague at the MIT Media Lab with over 100 patents and the chief scientist at C10 AI Ventures, believes that the traditional model of learning where what we learn before age 20-25 provides a 40-45 year career is no longer the case. Instead, we’re in a world where students are teaching us new things every day, and AI will play a crucial role in helping us learn how to learn new things more effectively.

Hari Balakrishnan, a professor in computer science and AI at MIT, agrees that AI will have a significant impact on education. He envisions a future where AI can personalize the learning experience, allowing human teachers to quickly assess where each student stands and tailor the instruction accordingly. This could enable education at scale, with students being able to learn remotely from teachers in different parts of the world.

Will AI Be More Physical?: From Implants To Practical Living

As AI continues to evolve, the question of how it will manifest in the physical world is a topic of great interest. Hari Balakrishnan is optimistic about the potential for AI to enhance our physical capabilities, particularly in the realm of health and wellbeing.

He foresees a future where AI-powered implants could improve our memory and overall cognitive function, serving as a kind of “assistant” to enhance our abilities. Additionally, Balakrishnan believes that within the next 20 years, we could see a significant increase in the number of vehicles on the road with some form of autonomous capabilities, potentially reaching 20-25% of the global fleet.

However, Balakrishnan also acknowledges the challenges of operationalizing AI in the real world, beyond just simulated environments. He believes that while there will be cases where AI completely replaces humans, in many other scenarios, the focus will be on how to integrate AI into existing workflows and business processes in a seamless and effective manner.

AI Shapes Learning For All Ages

The impact of AI on learning extends beyond just children in school. Rames Sarkar believes that the traditional model of a 40-45 year career based on what we learn before age 20-25 is no longer the case. Instead, we’re in a world where students are teaching us new things every day, and AI will play a crucial role in helping us learn how to learn new things more effectively.

Sarkar envisions a future where AI will help us become smarter, not just by automating the “drudge work,” but by empowering us to be better at tasks that were previously thought to be uniquely human, such as painting or songwriting. He believes that AI will create a new form of human-machine symbiosis, where the roles may shift between humans acting in a supervisory capacity and AI taking on a more supervisory role.

Balakrishnan agrees that AI will have a significant impact on education, allowing for more personalized learning experiences and enabling remote learning on a global scale. He also sees AI as a tool that can help address some of the challenges in less glamorous but vital sectors, such as water, health, and agriculture, by improving productivity and unit economics to make these areas more attractive to top talent.

AI In Governance: What’s Next?

The role of AI in governance and decision-making is another area of significant interest. Sarkar draws a parallel to the failed attempts of the Soviet Union to use optimization techniques to centrally plan their economy, noting that this approach is similar to how many organizations are currently using AI and data centralization today.

However, Sarkar believes that this model is likely to shatter, and we’ll see a shift towards a more decentralized approach, where AI is used in a more distributed manner. He sees the intersection of productivity gains in the real world and the ability to do this in a decentralized way as two major trends that will shape the future.

Balakrishnan agrees that the centralization of data and governance is a concern, as many organizations and entities are reluctant to share their data with a central authority. He envisions a future where specialized models and federated learning will allow for more autonomous decision-making at the local level, while still enabling collaboration and coordination when necessary.

AI And Crypto: How Or Will It Stabilize Cryptocurrency?

The relationship between AI and cryptocurrency is another area of discussion. Sarkar acknowledges the significant downsides of the current state of the crypto ecosystem, where lack of identity and proper safeguards has led to issues like theft, fraud, and even funding of illicit activities.

However, Sarkar believes that the future of decentralized finance and incentivization mechanisms holds promise, and that AI can play a role in designing more effective and responsible systems. He sees the potential for AI to act as a “scientist” in solving complex problems, as well as an “engineer” in designing and optimizing the systems and incentives that underpin these new financial models.

AI And Navigation: Uber, Lyft, Location Services

The impact of AI on transportation and navigation services is another area of focus. Balakrishnan predicts that within the next 20 years, we could see a significant increase in the number of vehicles on the road with some form of autonomous capabilities, potentially reaching 20-25% of the global fleet.

However, he also acknowledges that the real challenge will be in operationalizing AI in these real-world scenarios, beyond just simulated environments. Integrating AI into existing workflows and business processes will be a key focus, as companies seek to leverage the technology to improve efficiency and safety on the roads.

Generative AI: Crash Next Year And Rebounding

The discussion also touched on the current state of generative AI, with the panelists predicting a potential crash in the next 18 months, followed by a rebound in the years to come.

Sarkar believes that there is a tremendous amount of misinformation and overinvestment in certain areas of generative AI, which could lead to a significant correction. However, he also sees significant underinvestment in many other areas, particularly in real-world sectors that have been traditionally overlooked, such as water, health, and agriculture.

Balakrishnan agrees that the hype cycle for generative AI may be nearing its peak, but he emphasizes that the long-term potential of the technology remains promising. He sees the need for a more balanced approach, where the focus is on applying AI to solve real-world problems, rather than chasing the latest trends.

Conclusion

As we look to the future, the panelists paint a complex and nuanced picture of how AI will shape society over the next 20 years. While there are certainly challenges and risks to navigate, they also see tremendous potential for AI to enhance our physical and cognitive capabilities, revolutionize education, and tackle some of the world’s most pressing challenges.

The key, they argue, is to adopt a balanced and decentralized approach, where AI is integrated into existing systems and workflows in a way that empowers both humans and machines to work together more effectively. By harnessing the power of AI while also addressing the ethical and practical concerns, we can unlock a future where the benefits of this transformative technology can be realized for the betterment of society as a whole.