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InfoQ Homepage News Ai4 2023 Summary Day Two: AI Legal Issues, AI in Education & Deploying AI

Ai4 2023 Summary Day Two: AI Legal Issues, AI in Education & Deploying AI

Day Two of Ai4 2023 conference was held on August 9th, 2023, at the MGM Grand hotel in Las Vegas, Nevada. This two-day event is organized by Fora Group and includes tracks focused on various industries, including automotive, financial, healthcare, and government. The day began with six mainstage presentations from leaders in AI technology.

The first talk was a fireside chat on "Navigating the Legal Complexities of Cutting Edge AI," between Che Chang, general counsel at OpenAI and Ksenia Semenova, founder and editor-in-chief of Turing Post. Semenova asked Chang several questions about the global legal landscape surrounding AI, and particularly generative AI. Chang noted that AI models, at their core, are simply using historical data to make a prediction; when looked at this way, "you understand...90% of what you need to think about from a regulatory perspective." He also noted that "AI'' is just another term for "any behavior that a machine can do, that a person can do," and since there is no single law for regulating human behavior, it would not make sense to have a single regulation for machine behavior.

Next up was Aaron Cheng, vice president of data science and solutions at dotData, Inc., speaking on "The Million-Dollar Problem: How to Make My Data Ready for AI?" Cheng's main thesis was that although raw data is very valuable, it is not ready for use in machine learning; he made the analogy of raw data to crude oil and "AI-ready" data to gasoline. The refining process used to get AI-ready data is feature engineering. He ended his talk with a case-study of a customer using his company's feature engineering platform.

The third talk was "Harnessing AI for Education So All Students Benefit," presented by Sal Khan, founder and CEO of Khan Academy. Khan began with a recap of his company's founding story, and then discussed Benjamin Bloom's Two-Sigma Problem, which shows how one-on-one tutoring can give students a two standard deviation improvement in academic performance. Khan now believes that generative AI is almost good enough to approximate a one-on-one tutor, which could give every student this advantage. Although he was initially "bummed" by the news headlines about cheating which accompanied the release of ChatGPT at the end of 2022, he soon came to realize it was a positive development, since it "forced people to grapple with" the challenges of using generative AI in education. Khan concluded his talk with demo videos of Khan Academy's new AI assistant, Khanmigo.

The next speakers were Jim Rowan, principal at Deloitte, and Jatin Dave, senior manager at Deloitte, speaking on "Establishing an AI Center of Excellence." They noted that a majority of companies have not figured out how to generate value from their AI investments, and their thesis was that an AI Center of Excellence (CoE) would help companies achieve that value. They listed four standard operating principles: a plan for embedding AI in the core business; focus on observable business impact; a comprehensive view of the AI tech stack; and a lookout for external disruptions. They also listed four pitfalls: lack of shared vision across business units; lack of executive sponsorship; the AI CoE in a support role instead of leading; and incoherent metrics for the CoE.

Next up, Solmaz Rashidi, chief analytics officer at The Estée Lauder Companies, spoke on "The Good, Bad, and Realities of Deploying AI Projects Within Enterprises." Rashidi began with statistics about AI initiatives and potential economic impact. She then shared a flowchart that executives could use to identify if a technology truly is AI. She concluded with an eight-point framework for enterprise AI deployments.

The final talk was another fireside chat, "The Past, Present, and Future of Enterprise AI," between Igor Jablokov, CEO of Pryon and Scott Pobiner, head of UX strategy, AI and data practice at Deloitte. Starting with the past, Jablokov recounted his previous efforts in AI, including developing technology used by Amazon Alexa and IBM Watson. He pointed out that the latest generative AI models are "nothing new," they simply have finally gotten attention from normal people. He also lamented that internet search results, which used to return "innovative creations of other fellow human beings," would soon become a "hall of mirrors" of AI-generated pages. He also cautioned against the adoption of models such as Llama, which appear to be open-source, but do in fact have several restrictions on their use.

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