If we believe we should leave everything to technology to solve all of our problems, we might be making a big mistake. That's the core messages from deep thinker and thought leader Daniel Smachtenberger. Daniel is specialized in catastrophic risk analyses. And he's showing us a way out, or better said, he has the capacity to think himself a way out to…well, most of our current big issues. A major one is our exponentially growing big tech.

Once just science fiction, the use of artificial intelligence is taking hold across industries and governments in a multitude of use cases. But these days we're not so much worried about being overthrown by our robot minions like in so many movies. Rather, there are bigger questions that impact our lives today. For instance, how and when should we share data for the greater good and when should we keep it for proprietary uses? Are particular artificial intelligence use cases, like facial recognition, ethical?

When engaging in argumentative discourse, skilled human debaters tailor claims to the beliefs of the audience, to construct effective arguments. Recently, the field of computational argumentation witnessed extensive effort to address the automatic generation of arguments. However, existing approaches do not perform any audience-specific adaptation. In this work, we aim to bridge this gap by studying the task of belief-based claim generation: Given a controversial topic and a set of beliefs, generate an argumentative claim tailored to the beliefs. To tackle this task, we model the people's prior beliefs through their stances on controversial topics and extend state-of-the-art text generation models to generate claims conditioned on the beliefs. Our automatic evaluation confirms the ability of our approach to adapt claims to a set of given beliefs. In a manual study, we additionally evaluate the generated claims in terms of informativeness and their likelihood to be uttered by someone with a respective belief. Our results reveal the limitations of modeling users' beliefs based on their stances, but demonstrate the potential of encoding beliefs into argumentative texts, laying the ground for future exploration of audience reach.

The six answers you want to have about Machine Learning, all in one place. The founder of Pinboard, Maciej Cegłowski, has just published his statement about "Privacy Rights and Data Collection in a Digital Economy". The addendum on Machine Learning of that document is a great, simple explanation of its intrinsical limits, and the risks coming from them. To make them even simpler to understand, I took the liberty of synthesizing it in an easier Q&A format. Questions and parts in italic are my own additions, and any error is mine only.

Two tech and beauty companies have come together in promoting inclusivity and diversity as the answers to bias-free AI in smart beauty technology. "The limit in diversity does not exist" Atima Lui, the Chief Marketing Officer and Dr. Taleb Alashkar, CTO and Co-Founder, of AlgoFace, told The Sociable that inclusivity and bias control are the new vision of AlgoFace. "AlgoFace's mission and goal is to build the most accurate unbiased face AI in the world, and this messaging is all about inclusivity. "We want our products to work on all skin tones, people of all physical abilities, people of all genders. I like to say that the limit in diversity does not exist," says Lui. AI and Augmented Reality (AR) are helping consumers in the beauty industry get the exact shade of makeup they need. "Certainly, bias is a big issue in this space.

Public debate forums provide a common platform for exchanging opinions on a topic of interest. While recent studies in natural language processing (NLP) have provided empirical evidence that the language of the debaters and their patterns of interaction play a key role in changing the mind of a reader, research in psychology has shown that prior beliefs can affect our interpretation of an argument and could therefore constitute a competing alternative explanation for resistance to changing one's stance. To study the actual effect of language use vs. prior beliefs on persuasion, we provide a new dataset and propose a controlled setting that takes into consideration two reader level factors: political and religious ideology. We find that prior beliefs affected by these reader level factors play a more important role than language use effects and argue that it is important to account for them in NLP studies of persuasion.

Peter Donnelly asks: "Why rage against machines when we could be friends?" Unfortunately, he neglects to mention the way the technology can be exploited to the detriment of individuals and communities. We(???) gave a similar upbeat prediction of the benefits information technology could provide when it first appeared some decades ago and, indeed, continue to do so. Much of this is justified – information technology has transformed our capabilities and in doing so has been of huge benefit to mankind in many domains. But some of that capability has been exploited by our dark side, ranging from pornography to criminal activities, fraud, trolling and hacking, taking in controversial surveillance and threats to privacy. Much of the current discussion in information technology communities is devoted to ways of fighting the dark side and organisations increasingly deploy more of their resources to fighting off or repairing the damage from the "bad guys".

HBO has spared no expense in bringing Jonathan Nolan's and Lisa Joy's expanded interpretation of Michael Crichton's cult 1973 film, Westworld, to life. The basic premise remains the same in that Westworld is a futuristic theme park where the rich can live out a Wild West fantasy by interacting with androids. In Hollywood terms, it's Jurassic Park (another Crichton creation) meets Deadwood (a classic and traditional HBO Western series). Westworld is the brainchild of Dr. Robert Ford (played by Anthony Hopkins), the creative director, chief programmer, and founder of the high-tech destination. Helping to bring this next-generation alternate reality world to life is Bernard Lowe (played by actor Jeffrey Wright of HBO's Boardwalk Empire and The Hunger Games).