The field of artificial intelligence is detonating with products like IBM Watson, DeepMind's AlphaZero, and voice recognition used in virtual assistants including Amazon's Alexa, Apple's Siri, and Google's Home Assistant. Due to the massive impact of AI on humans' lives, the concern is growing about how to adopt a sound ethical AI strategy to shape future developments. Building ethical AI requires both an ethical way for building AI systems and a strategy for making AI systems themselves moral. For instance, engineers of self-driving vehicles should consider their social results including guaranteeing that the vehicles are fit for making moral decisions. Subsequently, building ethical use of artificial intelligence that we can trust should be at the core of its plan and development. The process of building ethical AI, in any case, is definitely not straightforward.

Companies are leveraging data and artificial intelligence to create scalable solutions -- but they're also scaling their reputational, regulatory, and legal risks. For instance, Los Angeles is suing IBM for allegedly misappropriating data it collected with its ubiquitous weather app. Optum is being investigated by regulators for creating an algorithm that allegedly recommended that doctors and nurses pay more attention to white patients than to sicker black patients. Goldman Sachs is being investigated by regulators for using an AI algorithm that allegedly discriminated against women by granting larger credit limits to men than women on their Apple cards. Facebook infamously granted Cambridge Analytica, a political firm, access to the personal data of more than 50 million users.

There is a school of thought that ponders a dark, dystopian future where artificially intelligent machines brutally and coldly run the world, with humans as only a biological tool. From Hollywood blockbusters, to evangelic tech entrepreneurs, we've all been exposed to the possibility of this type of future, but have we all stopped to ponder how we should avoid it? Now, of course, all of this dystopia is many many decades away, and only one of several gazillion possible future outcomes. But that doesn't preclude getting the conversation started today. For me, and many others, it boils down to one simple thing: ethics.

Artificial intelligence has disrupted every area of our lives -- from the curated shopping experiences we've come to expect from companies like Amazon and Alibaba to the personalized recommendations that channels like YouTube and Netflix use to market their latest content. But, when it comes to the workplace, in many ways, AI is still in its infancy. This is particularly true when we consider the ways it is beginning to change talent management. To use a familiar analogy: AI at work is in the dial-up mode. The 5G WiFi phase has yet to arrive, but we have no doubt that it will.

In October, Amazon had to discontinue an artificial intelligence–powered recruiting tool after it discovered the system was biased against female applicants. In 2016, a ProPublica investigation revealed a recidivism assessment tool that used machine learning was biased against black defendants. More recently, the US Department of Housing and Urban Development sued Facebook because its ad-serving algorithms enabled advertisers to discriminate based on characteristics like gender and race. And Google refrained from renewing its AI contract with the Department of Defense after employees raised ethical concerns. Those are just a few of the many ethical controversies surrounding artificial intelligence algorithms in the past few years.

Other local projects are working toward this progress, like the Chicago Data Collaborative, a partnered project of research and advocacy organizations to holistically understand policing data practices--including the use of AI--in order to examine whether such practices are discriminatory. And at events like Re-Imagined Cities, Chi Hack Night, and the Chicago City Data Users Group, our city's technologists regularly convene to discuss algorithmically aided decision-making and ethical use of public datasets, as well as ethical and equitable tech practices among governments and private entities more broadly.

Google's collaboration with the Department of Defense to develop AI system's for the US military's fleet of war drones, dubbed Project Maven, proved a double-edged sword for the technology company. On one hand, the DoD contract was quite lucrative, worth as much as $250 million annually. On the other hand, public backlash to the news that the company was helping the government build more efficient killing machines was immediate, unwavering and utterly ruthless. A dozen employees quit the company in protest, another 4,000 petitioned management to terminate the contract outright. The uproar was so deafening that Google had to come out and promise to not renew the deal upon its completion next year.

There is a school of thought that ponders a dark, dystopian future where artificially intelligent machines brutally and coldly run the world, with humans as only a biological tool. From Hollywood blockbusters, to evangelic tech entrepreneurs, we've all been exposed to the possibility of this type of future, but have we all stopped to ponder how we should avoid it? Now, of course, all of this dystopia is many many decades away, and only one of several gazillion possible future outcomes. But that doesn't preclude getting the conversation started today. For me, and many others, it boils down to one simple thing: ethics.

Montreal-based Element AI has expanded to London, UK. Dr. Julien Cornebise, a former DeepMind scientist, will lead the lab as director of research. Cornebiese was an early employee of Deepmind before it was acquired by Google in 2012. He created and led the Health Applied Research Team, and has been working with Amnesty International since he left DeepMind in 2016. The company says that it's focusing on'AI for good' through this office, while also expanding its network of researchers, scientists, and the private and public sector.