So now, without any further ado let's dive into the how the self-driving car industry looked like 15–20 years ago! Unless you are living under a rock, you probably know that the self-driving car industry has become one of the hottest industries in the last 5–10 years. Some of the world's biggest companies like Google, Tesla, GM are working on self-driving cars. These companies have spent more than 120 billion dollars on self-driving car R&D just in 2020 alone! The CEOs of these companies are saying that they are on the verge of creating the driverless cars that we all imagine when we think about our future cities(the ones where you can just fall asleep in to get the extra hour of sleep).

Monica Lam is a Professor in the Computer Science Department at Stanford University since 1988. She is the faculty director of the Open Virtual Assistant Lab (OVAL). She received a B.Sc. from University of British Columbia in 1980 and a Ph.D. in Computer Science from Carnegie Mellon University in 1987. Monica is a Member of the National Academy of Engineering and Association of Computing Machinery (ACM) Fellow. She is a co-author of the popular text Compilers, Principles, Techniques, and Tools (2nd Edition), also known as the Dragon book.

What do you do for a living? How do you explain your job to people outside of your field? I work as an Engineering Manager for the Machine Learning team on the Identity product at Stripe. For those outside tech, I define machine learning as the technology that allows computers to look at data and learn patterns from it which in turn helps us make predictions when the computer sees new data in the future. My team is responsible for building machine learning systems and models for Stripe's new identity product.

GoGuardian is a software company that makes, essentially, spyware: software that helps teachers and schools block and monitor what kids are doing online. When a student is using a school-issued Chromebook that has GoGuardian on it, the teacher can see just about everything they're doing. These technologies have been embraced by teachers and state Departments of Education alike, but students are less enthralled with having their online lives constantly surveilled. On Friday's episode of What Next: TBD, I spoke with Priya Anand, a tech reporter for Bloomberg who wrote a story on GoGuardian, about the rise of the school surveillance state and the implications of this technology for student's mental health and privacy. Lizzie O'Leary: You wrote for Bloomberg about Pekin Community High School in Illinois, which has been using GoGuardian for three years.

Emory University's Department of Economics hosted an event about artificial intelligence's impact on growth, jobs and inequality on Oct. 27.

Automated One-way Interview is an interviewing method for the recruiter to assess the candidate without actually spending real-time interviewing them. Real-time interviews require either the interviewer or candidate to travel and spend a significant amount of time. On the other hand, automated interviewing mode lets the recruiter send a set of questions to the candidate and allows the candidate to answer and send them back at their own comfort. There is a reason why every bit of technology is evolved and acing automated or one-way interview depends on how good a candidate understands the recruiter's motive behind it. This is the exact reason why TurboHire's one-way video interviewing took birth.

How would an AI writing program start an article on the future of AI writing? Well, there's one easy way to find out: I used the best known of these tools, OpenAI's GPT-3, to do the job for me. Using GPT-3 is disarmingly simple. You have a text box to type into and a menu on the side to adjust parameters, like the "temperature" of the response (which essentially equates to randomness). You type, hit enter, and GPT-3 completes what you've written, be it poetry, fiction, or code.

What is the future of responsible AI in the UK? There is growing recognition, as AI is increasingly present in our lives, that it must be responsibly deployed. But what does this mean in practice? And what does it mean specifically here, in the UK? AI tools offer great opportunities. Data science and machine learning techniques are increasingly deployed in industry, and might be applied, for instance, to support sustainable development initiatives, improve educational outcomes, or enhance human welfare more generally.

In the coming decade, I expect that AI will play an increasingly prominent role in the lives of people everywhere. AI-infused services will become more common, and AI will become increasingly embedded in the daily lives of people across the world. I believe that this will bring with it great economic and societal benefits, but that it will also require us to address the many challenges to ensure that the benefits are broadly shared and that people are not marginalised by these new technologies. A key insight of AI research is that it is easier to build things than to understand why they work. However, defining what success looks like for an AI application is not straightforward.

What do you think of when you hear the word automation? None of this is wrong, per se, but we like to add another word when we think about automation: productive. For us, automation is all about giving humans superhero capes. We think about it as a way for productive automated work technologies to amplify humanness and economic productivity. Or, instead of focusing on how automation replaces humans, honing in on how it can improve our work.