A.I.’s Original Sin

A growing number of lawsuits complain that AI tools are being trained and producing content based on copyrighted material, which threatens the livelihoods of authors, artists, and other creators. Courts are in the early stages of determining whether AI companies’ use of copyrighted materials to train, create, and sell content nearly indistinguishable from that of creators is fair use or copyright infringement.

ChatGPT's popularity has ignited intense competition among tech giants to lead the AI chatbot market. Microsoft, Google, Amazon, and Meta are all rapidly developing conversational AI tools and aggressively integrating them into products in hopes of reshaping the search engine, productivity software, and consumer electronics markets.

Artificial Intelligence could revolutionize every aspect of our lives, but only if we can develop AI that reliably carries out its tasks. While some see AI as a cornucopia that will free the human race from drudgery, others see dangers in ceding so much power to digital, non-human minds. In Rebooting AI, Gary Marcus and Ernest Davis argue that modern AI underdelivers on its promise while AI proponents oversell what it can do. Marcus and Davis are AI advocates who feel that current AI research is heading in the wrong direction, with its narrow focus on “big data” and machine learning.

In this guide, we’ll examine how the public perception of modern AI differs from reality, how AI works, and the many ways in which it fails. We’ll then describe Marcus and Davis’s prescription for producing stronger AI systems to benefit the human race. We’ll also highlight where modern AI trends are leading, other experts’ thoughts on machine cognition, and how AI development is affecting business and society at large.

The New York Times recently signaled a major copyright battle in suing OpenAI and Microsoft, alleging unauthorized use of its content to train their AI chatbots. The lawsuit could change copyright laws and set a precedent that shapes future disputes over AI use of copyrighted material.

A growing number of lawsuits complain that AI tools are being trained and producing content based on copyrighted material, which threatens the livelihoods of authors, artists, and other creators. Courts are in the early stages of determining whether AI companies’ use of copyrighted materials to train, create, and sell content nearly indistinguishable from that of creators is fair use or copyright infringement.

With the artificial intelligence (AI) market projected to hit $1.3 trillion over the next decade, companies are scrambling to train their AI products so that they’re poised to get a piece of the pie. However, training AI comes with hidden costs. These include exploitative labor practices in developing countries and refugee camps, where desperate workers toil in “digital sweatshops” and make barely enough money to make ends meet.

Model collapse is the complete erosion of AI models that occurs when they’re trained on flawed content generated by other AI models. Model collapse can lead to nonsensical, inaccurate, and biased AI output. Experts say that diverse, human-curated data is key to stopping AI model collapse.

In the thought-provoking episode of Huberman Lab, Dr. Andrew Huberman invites Marc Andreessen to dive deep into the core aspects of innovation, societal impact, and the role of institutions in driving reform. Their dynamic conversation surgically dissects the traits needed for successful innovation, the vital role of risk-taking, and the significance of innovation in societal transformation. Andreessen identifies certain personality traits key to successful innovation and discusses the power of a like-minded community in supporting innovation amidst a culture of intolerance.

The discussion doesn't stop there. Andreessen and Dr. Huberman further explore the implications of advancements in technology, such as Artificial Intelligence (AI), on societal norms and ethics, and the potential these advancements hold for sectors like healthcare. They also discuss the rising public concerns around gene-editing technologies and nuclear energy. The societal fears, potential risks, and transformative impacts of these technological innovations form an essential part of the conversation. Overall, this engaging podcast episode is an insightful exploration into the transformative power of innovation and risk-taking in our ever-evolving society.

Artificial Intelligence could revolutionize every aspect of our lives, but only if we can develop AI that reliably carries out its tasks. While some see AI as a cornucopia that will free the human race from drudgery, others see dangers in ceding so much power to digital, non-human minds. In Rebooting AI, Gary Marcus and Ernest Davis argue that modern AI underdelivers on its promise while AI proponents oversell what it can do. Marcus and Davis are AI advocates who feel that current AI research is heading in the wrong direction, with its narrow focus on “big data” and machine learning.

In this guide, we’ll examine how the public perception of modern AI differs from reality, how AI works, and the many ways in which it fails. We’ll then describe Marcus and Davis’s prescription for producing stronger AI systems to benefit the human race. We’ll also highlight where modern AI trends are leading, other experts’ thoughts on machine cognition, and how AI development is affecting business and society at large.