It seems a simple question, but it's one without simple answers. That's particularly true in the arcane world of artificial intelligence (AI), where the notion of smart, emotionless machines making decisions wonderfully free of bias is fading fast. Perhaps the most public taint of that perception came with a 2016 ProPublica investigation that concluded that the data driving an AI system used by judges to determine if a convicted criminal is likely to commit more crimes appeared to be biased against minorities. Northpointe, the company that created the algorithm, known as COMPAS, disputed ProPublica's interpretation of the results, but the clash has sparked both debate and analysis about how much even the smartest machines should be trusted. "It's a really hot topic--how can you make algorithms fair and trustworthy," says Daniel Neill.

Algorithms, machine learning and, more broadly, artificial intelligence (AI) promise to introduce astounding levels of efficiencies to cities' monitoring of citizens and infrastructure, their planning and governance, and their service response and decision-making. While we have yet to automate all of our planning and resource allocation decisions, advances in machine learning and neural networks, as well as our ability to collect data through even more network sensors, are bringing automation at least to certain parts of our civic problem-solving processes. One well known and somewhat contentious example is the use of predictive crime analytics to dispatch police units proactively, in anticipation of crime incidents. These tools may be branded, and even sold, under that catch-all name of artificial intelligence and packaged in smart city solutions such as the NVIDIA Metropolis platform. However optimistic we are about the potential for AI and algorithms to "do good," their positive social impact remains far from guaranteed without adequate regulation to ensure social accountability, reduction of harm, and compliance with legal rights and protections.

Steven Pinker is a cognitive psychologist, linguist, and author of Bill Gates' two favorite books. However, his latest – Enlightenment Now – has some serious shortcomings centering on Pinker's misperceptions about climate change polarization. Pinker falls into the trap of'Both Siderism,' acknowledging the Republican Party's science denial, but also wrongly blaming liberals for the policy stalemate, telling Ezra Klein: There are organizations like Greenpeace and NRDC who are just dead set opposed to nuclear. There are also people on the left like Naomi Klein who are dead set against carbon pricing because it doesn't punish the polluters enough ... the people that you identify who believe in a) carbon pricing and b) expansion of nuclear power, I suspect they're a tiny minority of the people concerned with climate … What we need are polling data on how many people really would support carbon pricing and an expansion of nuclear and other low carbon energy sources. Here Pinker has created a strange straw man that bears no resemblance to the real population of American liberals and environmentalists.

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. At Apple's near-sacred product unveiling event last year, the iPhone X was undoubtedly the star of the show. Among its most boasted about features? Rather than asking users to use their fingerprint on the now-nonexistent home button to unlock their phones, the iPhone X's Face ID uses its cameras to make 3-D scans of their faces, which then enable them to unlock their phones by just holding the device up to their mugs. At the event, an exec boasted that the facial recognition technology proved far safer than its previous fingerprint-based Touch ID, claiming that there's only a 1 in a million chance of a random stranger's face unlocking a user's device.

Emma Watson displayed some new ink at the Vanity Fair Oscar Party but social media users pointed out the tattoo's glaring grammatical error. The "Harry Potter" star showed off a tattoo that read "Times Up" on her arm -- clearly missing the apostrophe for the organization Time's Up. It was not immediately clear if the tattoo was real. People reported the tattoo could be be temporary. The Brown University graduate has been an outspoken proponent of the Time's Up movement, which began after bombshell exposés revealed decades of alleged sexual misconduct by Hollywood producer Harvey Weinstein.

We are not only living in an age where women are being under-represented in many spheres of economic life, but technology could make this even worse. Women hold just 19% of board directorships in the US and Europe. This gender gap in the boardroom persists, despite the fact that, on average, women have obtained higher educational qualifications than their male counterparts for more than two decades in many OECD countries. And the main reason is social bias.

Until recently, when automated technologies emerged there was a gap between the laborers it replaced and the decision-makers who implemented it. The CTO for a car manufacturer could safely implement factory automation that laid off portions of the workforce five steps below him without fearing for his own livelihood. But as AI has matured, it's begun to climb the corporate ranks, going after positions that require advanced degrees and high IQs. No longer do the higher-ups make decisions that result in the lower-downs being laid off. Instead, disruptive startups are offering AI services that can replace entire professions with lower prices and more precise results.

"We expect global investment in artificial intelligence to continue at a rapid pace, as the underlying technologies supporting AI mature and both incumbent banks and fintechs look to find ways to embed financial services offerings into home automation systems and other IoT enabled products," he says. Given financial services is highly regulated, the deployment of AI in banking will be accompanied by deep consideration of ethics and legal liability. As Microsoft's managing director, Steven Worrall, will tell The Australian Financial Review Business Summit on Wednesday – in a special session on the impact of disruptive technologies – artificial intelligence can be used to help solve big problems, but just because technology can do something, doesn't mean it should.

Turkish lacks gendered pronouns: The single word "o" does the work that in English is done by "he," "she," or "it." That linguistic quirk poses a challenge for machine-translation tools: to render a Turkish sentence into English, a tool like Google Translate must guess its subject's gender -- and in the process, often betrays its own built-in biases. For example, Google translates the Turkish sentence "o bir doktor" as "he is a doctor" and the grammatically identical "o bir hem?ire" as "she is a nurse." Google's algorithms similarly assume that a president or entrepreneur is male, but that a nanny, teacher or prostitute is female. Even character traits come with assumed genders: A hardworking person is judged to be male, while a lazy one is assumed to be female.

Originally published by Scientific American. Law enforcement's use of predictive analytics recently came under fire again. Dartmouth researchers made waves reporting that simple predictive models--as well as nonexpert humans--predict crime just as well as the leading proprietary analytics software. That the leading software achieves (only) human-level performance might not actually be a deadly blow, but a flurry of press from dozens of news outlets has quickly followed. In any case, even as this disclosure raises questions about one software tool's credibility, a more enduring, inherent quandary continues to plague predictive policing.