In the previous two episodes, Bryson cut through the smoke and mirrors around resistance to AI regulation, and broke down the importance of due diligence in the software development process. In this final installment, Bryson revisits the challenge of rooting out AI bias, explains why machines won't take over the world, and reveals the secret to AI success. Hope you enjoy the conversation. Appian: Earlier you said that you don't think a company on a mission to "move fast and break things" will be able to prove they did due diligence, when bad things happen with their software. Bryson: No matter what industry you're in, you should be able to show that you followed very careful methods of software construction--including using machine learning.

People too often forget that IQ tests haven't been around that long. Indeed, such psychological measures are only about a century old. Early versions appeared in France with the work of Alfred Binet and Theodore Simon in 1905. However, these tests didn't become associated with genius until the measure moved from the Sorbonne in Paris to Stanford University in Northern California. There Professor Lewis M. Terman had it translated from French into English, and then standardized on sufficient numbers of children, to create what became known as the Stanford-Binet Intelligence Scale. The original motive behind these tests was to get a diagnostic to select children at the lower ends of the intelligence scale who might need special education to keep up with the school curriculum. But then Terman got a brilliant idea: Why not study a large sample of children who score at the top end of the scale?

Over the last few years, AI and machine learning technologies have been rapidly adopted by software vendors across all fields, from IT to analytics to data management. Oracle, one of the world's largest vendors in the enterprise IT space, is no exception. Last year, the vendor increased its AI tools with a major expansion to Oracle Adaptive Intelligent Apps, which sought to bring AI and machine learning capabilities to HR, finance, e-commerce and sales applications, among others. By bringing AI to its various platform offerings and to the cloud, the Oracle adaptive intelligence software looks to deliver machine learning capabilities that are ready to go and easy to use across a variety of domains -- even though the vendor is playing catch-up in some regards with the technology, which it refers to more informally as Oracle AI Apps. The interview was conducted at The AI Summit in San Francisco, where Oracle representatives presented a keynote.

When you are two years old, your mother knows more about you than you know yourself. As you get older, you begin to understand things about your mind that even she doesn't know. But then, says Yuval Noah Harari, another competitor joins the race: "You have this corporation or government running after you, and they are way past your mother, and they are at your back." Amazon will soon know when you need lightbulbs right before they burn out. YouTube knows how to keep you starting at the screen long past when it's in your interest to stop. An advertiser in the future might know your sexual preferences before they are clear to you. Recently, I spoke with Harari, the author of three best-selling books, and Tristan Harris, who runs the Center for Humane Technology and who has played a substantial role in making "Time Well Spent" perhaps the most-debated phrase in Silicon Valley in 2018. They are two of the smartest people in the world of tech, and each spoke eloquently about self-knowledge and how humans can make themselves harder to hack. As Harari said, "We are now facing not just a technological crisis but a philosophical crisis." Please read or watch the entire thing. This transcript has been edited for clarity. Nicholas Thompson: Tristan, tell me a little bit about what you do and then Yuval, you tell me too. Tristan Harris: I am a director of the Center for Humane Technology where we focus on re-aligning technology with a clear-eyed model of human nature. And I was before that a design ethicist at Google where I studied the ethics of human persuasion. Yuval Noah Harari: I'm a historian and I try to understand where humanity is coming from and where we are heading. NT: Let's start by hearing about how you guys met because I know that goes back a while. When did the two of you first meet? YNH: Funnily enough, on an expedition to Antarctica, we were invited by the Chilean government to the Congress of the Future to talk about the future of humankind and one part of the Congress was an expedition to the Chilean base in Antarctica to see global warming with our own eyes. And I think we particularly connected with Michael Sandel, who is a really amazing philosopher of moral philosophy. I would have loved to see the whole thing. You write about different things, you talk about different things but there are a lot of similarities. And one of the key themes is the notion that our minds don't work the way that we sometimes think they do. We don't have as much agency over our minds as perhaps we believed until now.

"One problem, say roboticists, is that robots often can't'see' behind leaves or reach behind a tree branch without potentially harming themselves or the fruit they're trying to grab," they report. "Roboticists are trying to solve these problems by enhancing the quality of sensors that allow robots to understand and navigate their surroundings." "RootAI, a Somerville, Mass., startup that is testing a prototype tomato picker, has started talking to seed developers who want to design crops that are more amenable to robotic harvesters." California's Driscoll's Inc., the world's largest berry distributor, is looking at raising its growing beds, making it easier for both robots and humans to pick fruit. HSBC's robot is boosting foot traffic in New York.

Here is a link to the podcast. Vicki: Thank you so much for having me. Hugo: It's an absolute pleasure to have you on the show. I'm really excited to talk about your work in Python education, full stack data science, end-to-end data science, what these things actually mean, and your work in consulting. Before we get into all of that, I'd love to know a bit about you. I'm wondering what you're known for in the data community. Vicki: Probably first and foremost, terrible puns and memes about all sorts of data and programming related things. My strategy is a little bit like BuzzFeed, right? Hit them with the memes and then sneak in serious content in between. Vicki: I've written a lot of blog posts about how to do specific things in Python, how to do specific things in data, and then just talking about like where we are in the data community in general, so very high level articles, and talking about things that break down complicated concepts into easy to understand analogies. I love that secondary is the content and that primary are terrible puns and memes. I don't mean to put you on the spot, but what's one of the worst puns you've said or come up with or heard? I have this series of puns where it's basically me pretending to talk to a TV producer to pitch them on possible shows or movies, and so that series is s pretty terrible series of tweets. I thought I would just mention that you're also, in terms of content, in the process of creating a DataCamp course.

The day started with 3 keynotes. David Patterson received a Turing Award in 2017 for his contribution in design and evaluation of computer architectures. In the talk he speaks about the end of Moore's law and it's impact on the industry. Given that hardware alone is not providing that much speed up anymore David Patterson sees a potential solution in creating Domain-Specific Architectures (DSA) and using Domain-Specific Languages (DSL) as a way to get high performance computation. As an example, he showed matrix multiplication in Python which can be speed up about 63000 times(!) if written in C and takes advantage of memory optimizations and vectorized instructions.

Read "technology" and "children" in the same sentence, and you'll probably think about screen time or social media. But technology's implications are vastly more profound: AI, machine learning, big data and automation will fundamentally reshape the lives of our youngest generation. How might we direct the power of emerging innovations to fulfill their rights? One trailblazer addressing this question is Erica Kochi, Co-Founder of UNICEF Innovation at the United Nations Children's Fund, who was named one of TIME's most influential people in the world. Erica continues to accelerate action – unveiling a new urban tech bets opportunity just this week – and to drive crucial dialogues as Co-Chair of the World Economic Forum's Global Future Council on Human Rights.

What do you mean by ethics for artificial intelligence? Well, that's a good starting point because there are different sorts of questions that are being asked in the books I'm looking at. One of the kinds of questions we're asking is: what sorts of ethical issues is artificial intelligence, AI, going to bring? AI encompasses so many different applications that it could raise a really wide variety of different questions. For instance, what's going to happen to the workforce if AI makes lots of people redundant? That raises ethical issues because it affects people's wellbeing and employment. There are also questions about whether we somehow need to build ethics into the sorts of decisions that AI devices are making on our behalf, especially as AI becomes more autonomous and more powerful. For example, one question which is debated a lot at the moment is: what sorts of decisions should be programmed into autonomous vehicles? If they come to a decision where they're going to have to crash one way or the other, or kill somebody, or kill the driver, what sort of ethics might go into that? But there are also ethical questions about AI in medicine. This might be useful since it seems people may sometimes open up more freely online. But, obviously, there are going to be ethical issues in how you're going to respond to someone saying that they're going to kill themselves, or something along those lines. There are various ethical issues about how you program that in. "AI is pushing us to the limits of various questions about what it is to be a human in the world" I suppose work in AI can be divided into whether you're talking about the sorts of issues which we're facing now or in the very near future. The issues we are facing now concern'narrow' AI which is focused on particular tasks.

The word "chaos" comes up often in an interview with Solon Angel, founder and chief strategy officer of Mindbridge Analytics Inc. He grew up in the Caribbean and France, where he dealt with discrimination, family instability and violence. Today the Ottawa-based entrepreneur says he's "comfortable" with the other kind of chaos, that which comes naturally in a tech startup. After the 2008 global financial crisis, Mr. Angel aimed to come up with something that might keep it from happening again. In 2015, he launched Mindbridge with the goal of transforming the financial auditing business with machine learning, or artificial intelligence.