We've reached a tipping point where it is now high time that we start the conversation of regulating Face Recognition Artificial Intelligence (AI). In a previous post, I explored some ideas of how we may regulate AI. I looked at several regulations in other fields and explored how they might apply for AI. The most compelling argument against AI regulation has been that it isn't clear for many as to precisely what needs to be regulated. However, in recent days, it has come to my attention that a specific kind of AI algorithm needs serious thought for regulation.

Summary: A number of major companies are experimenting with artificial intelligence tools to cut back costs for legal work and speedup the menial jobs. Walmart is the leader in cutting costs. These cost cutting methods are moving into their legal work but they are not alone. Walmart, Nationwide and a number of other companies are taking advantage of Artificial Intelligence to redirect work. AI tools are able to "draft contracts, write answers to legal complaints, or answer simple questions," according to Big Law Business.

Artificial intelligence tools can draft contracts, write answers to legal complaints, or answer simple questions. They may not replace a lawyer's to-do list, but they could save time. Walmart and Nationwide Insurance are among the companies experimenting with how artificial intelligence tools can streamline their in-house legal departments and their work with outside counsel, and save money in the process. The use of more advanced data tools also is a growing cost-saving trend. That ultimately could drive law firms to change their thinking.

Tech companies are investing major resources into developing virtual assistants, making calculated bets that these digital entities will be the future of mobile computing. Apple first made the idea mainstream when it launched Siri with the iPhone 4S in 2011. Google followed swiftly with the launch of its A.I.-fueled Google Now (which has since evolved into Google Assistant) in 2012. Apple had a three-year head start on other major competitors such as Amazon's Alexa and Microsoft's Cortana. But while Apple took the early lead in the space, its cautious approach--particularly when it comes to integrating information and functionality from third-party apps--has left it lagging.

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The gambling industry is increasingly using artificial intelligence to predict consumer habits and personalise promotions to keep gamblers hooked, industry insiders have revealed. Current and former gambling industry employees have described how people's betting habits are scrutinised and modelled to manipulate their future behaviour. "The industry is using AI to profile customers and predict their behaviour in frightening new ways," said Asif, a digital marketer who previously worked for a gambling company. "Every click is scrutinised in order to optimise profit, not to enhance a user's experience." "I've often heard people wonder about how they are targeted so accurately and it's no wonder because its all hidden in the small print."

Lawyers at some of the biggest firms in London expect job losses in their workplaces because of artificial intelligence. Research from commercial property company CBRE has found that nearly half of the largest law firms in London think that junior and support roles will be reduced due to the introduction of artificial intelligence. The effect of artificial intelligence on employment is hotly contested, with some arguing that we can expect a high level of automation, to such an extent that it will be necessary to re-think economic models and the role of taxation. Others believe that though AI will take some jobs, it will also create an equal number of new roles. RELATED: Can we have ethical artificial intelligence?

Artificial intelligence brings tremendous opportunity for business and society. But it has also created fear that letting computers make decisions could cause serious problems that might need to be addressed sooner rather than later. Broadly speaking, AI refers to computers mimicking intelligent behavior, crunching big data to make judgments on everything from how to avoid car accidents to where the next crime might happen. If a computer consistently denies a loan to members of a certain sex or race, is that discrimination? Will regulators have the right to examine the algorithm that made the decision? Some big technology companies are seeking to set ethical standards through alliances with futurists, civil-rights activists and social scientists--which critics see as an effort to prevent regulation by government.

Journal of Parallel and Distributed Computing 104, 19-35.

Perhaps the trick is to start small. At the EmTech Digital conference on AI in San Francisco this week, Microsoft Research Postdoctoral Researcher Timnit Gebru suggested taking cues from the field of hardware design. To understand what problems this would solve, it helps to have a clear idea of exactly how bias in AI works. A typical AI is trained on data from the past, looks for patterns in that data, then makes predictions about the future. So if your dataset is racist or sexist–and much data is–the AI will generalize from that bias and exacerbate it.