AI has transitioned from an era of novelty to the era of the fake out. Fake is everywhere: in the news, in bots trolling Twitter, in scam emails that no longer have human authors. Even the legitimate A may be overdoing the “fake”, substituing human performance with machine performance, often by making allowances for lower and somewhat altered quality.
There are limits to the profitability of these techniques, and increasingly signs of consumer fatigue are evident in response to whiz bang AI. Researchers and consumers alike recognize a need for less eery and uncomfortable deployment of AI in the marketplace, in law, and in society.
Aileen Nielsen offers an overview of how law and consumer behavior alike increasingly require a more “authentic” AI and how business leaders are responding to this need. Along the way, Aileen explores how the current state of the art in machine learning and deep learning can respond to this desire from AI end users. She concludes with thoughts on how cutting-edge technical research is likely to lead to authenticity breakthroughs.
Aileen Nielsen works at an early-stage NYC startup that has something to do with time series data and neural networks, and she’s the author of a Practical Time Series Analysis (2019) and an upcoming book, Practical Fairness, (summer 2020). Previously, Aileen worked at corporate law firms, physics research labs, a variety of NYC tech startups, the mobile health platform One Drop, and on Hillary Clinton’s presidential campaign. Aileen is the chair of the NYC Bar’s Science and Law Committee and a fellow in law and tech at ETH Zurich. Aileen is a frequent speaker at machine learning conferences on both technical and legal subjects.
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