Since she was a kid, Assia Boundaoui knew that she, her family and her neighbors were being watched. It was an open secret in her hometown of Bridgeview, a Chicago suburb home to a large Muslim and Arab population where for decades residents experienced government surveillance, including home visits by FBI agents. Using her training as a journalist and documentary filmmaker, Boudaoui sought out proof beginning in 2014 by interviewing community members and filing Freedom of Information requests for records on Operation Vulgar Betrayal, one of the largest pre-9/11 counterrorism probes conducted domestically in the United States and included the Bridgeview community. She also submitted hundreds of privacy waivers on behalf of people who were surveilled to the Department of Justice, requesting files on individuals who had experienced surveillance. When the FBI responded, ultimately saying it would take years to process 33,000 pages of records on the investigation, Boundaoui sued. In 2017, a federal judge ruled that she was entitled to expedited processing, ordering the FBI to release 3,500 pages from the Vulgar Betrayal file each month and to give priority to the sub files of individuals for whom privacy waivers were filed.

Imagine: in 2001 Steven Spielberg released his science fiction movie called "Artificial Intelligence". Artificial intelligence programming is one of the hottest topics in the tech world today, and many influencers, from late, great Stephen Hawking to increasingly popular Elon Musk, both embrace the achievements of AI projects and warn us about the possible implications. So how does this new technology influence the world around us? Should you be worried that some AI robot will steal your job any time soon? Both academic and industrial researchers have put a lot of effort into creating adaptable smart machines for all sorts of industrial processes. Many startups have caught the trend and are beginning to develop reinforcement learning algorithms for industrial robotics.

This is a quick transcript of the interview of Peter Norvig by Lex Fridman. I find this interview so interesting and revealing, that I decided to take on the task of making a transcript of the interview published in YouTube. Lex Friedman: The following is a conversation with Peter Norvig. A Modern Approach", and educated and inspired a whole generation of researchers, including myself, to get into the field of Artificial Intelligence. This is the Artificial Intelligence podcast. Lex Fridman: Most researchers in the AI community, including myself, own all three editions, red green and blue, of the "Artificial intelligence, a modern approach", the field defining textbook. As many people are aware that you wrote with Stuart Russell, how is the book changed, and how have you changed in relation to it from the first edition to the second, to the third, and now fourth edition as you work on it? Peter Norvig: Yeah so it's been a lot of years, a lot of changes. One of the things changing from the first, to maybe the second, or third, was just the rise of computing power, right? So, I think in the First Edition we said: "here's predicate logic but that only goes so far because pretty soon you have millions of short little medical expressions and they can possibly fit in memory, so we're gonna use first-order logic that's more concise." And then we quickly realized: "Oh, predicate logic is pretty nice because there are really fast Sat solvers, and other things, and look there's only millions of expressions and that fits easily into memory, or maybe even billions fit into memory now.

With advances in artificial-intelligence technology occurring more rapidly than ever, the potential for AI to assist us in nearly everything we do at work and at home has become very real. However, some fear that along with AI's tremendous upside of delivering efficiencies humans could not possibly realize on their own comes a dark side--the possibility that super-intelligent AI machines could develop complete autonomy and act against human interests. Earlier this year at the AI Frontiers conference in Santa Clara, California, we sat down with AI experts from some of the world's leading technology-first organizations to find out if fears about AI overtaking humankind have any founding. An edited version of their remarks follows. Adam Coates, director, Baidu Research Silicon Valley AI Lab: I do think sometimes we get carried away and start to think about sentient machines--machines that are just going to understand everything the way that we do and totally interact with us like a human.

Bruno Osorio is the vivid example of overcoming. At the age of 30, Bruno leads the Adamastor Studio, a video game developer working on a VR music project to be launched exclusively on Sony's Playstation 4. Bruno's perseverance not only has taken him and his small Portuguese studio to work hand in hand with one of the biggest companies in the world, but also turning his childhood passion, video games, into his current lifestyle. Now, the studio is expanding its horizons to translate exclusive aspects of games to other scenarios in the form of gamification solutions. Being an entrepreneur and making a living out of your dream is definitely something many would like to achieve, but in Bruno Osorio's shoes, it was just a matter a of time before it came true. Bruno is decisive, ambitious and mature, and his physical condition – Bruno suffers from a cerebral palsy – has not retained him for what he has always wanted to become. Intelligenthq: At the age of 30, you are running the Adamastor Studio developing video-games as well as providing other services, what's it like to create a new business, in this case a studio?

Although they may not yet be anticipating it, candidates can now participate in an initial screening from their own homes by an AI-based video interview bot using their computer or mobile phone screen. Applicants' responses are analyzed by an AI system using machine learning algorithms and natural language processing to consider their answers, word choices, body language, and tone of voice. The video interview analytics can be used by the AI to select the candidates whose skills and abilities are well-aligned with the positions they have applied for by matching their profiles with those of successful employees. The AI can then invite successful candidates to in-person interviews.

"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.

I'm going to lead with the punchline on this one. I believe that LPI should invest in providing a certification path for some kind of machine learning, specifically geared to open source development in artificial intelligence. Whatever you may think about automation and artificial intelligence from the perspective of what it will eventually mean for humanity, there's no question that some form of artificial intelligence is present in every aspect of our lives. Those of us who own one or more Google Home or Alexa speakers know full well how much AI touches our lives. Smart systems like Google's Assistant are built using TensorFlow ( https://tensorflow.org), an open source programming library that has become a kind of goto set of tools for anyone building machine learning, deep learning, natural language processing (as in your smart speaker), or neural network based applications.

Yoshua Bengio is recognised as one of the world's leading experts in artificial intelligence and a pioneer in deep learning. Following his studies in Montreal, culminating in a PhD in computer science from McGill University in 1991, Professor Bengio did postdoctoral studies at the Massachusetts Institute of Technology (MIT) in Boston. In 2019, he was awarded the Killam Prize as well as the 2018 Turing Award, considered to be the Nobel prize for computing. These honours reflect the profound influence of his work on the evolution of our society. Yoshua Bengio is also known for collecting the largest number of new citations in the world in the year 2018.

In this episode I have a conversation with Filip Piękniewski, researcher working on computer vision and AI at Koh Young Research America. His adventure with AI started in the 90s and since then a long list of experiences at the intersection of computer science and physics, led him to the conclusion that deep learning might not be sufficient nor appropriate to solve the problem of intelligence, specifically artificial intelligence. I read some of his publications and got familiar with some of his ideas. Honestly, I have been attracted by the fact that Filip does not buy the hype around AI and deep learning in particular. He doesn't seem to share the vision of folks like Elon Musk who claimed that we are going to see an exponential improvement in self driving cars among other things (he actually said that before a Tesla drove over a pedestrian). I have a somewhat complex love and hate relationship with deep learning.