After gaining the highest amount of venture funding in 2014, the healthcare industry became a viable target for startups. The US healthcare system is now worth $3,504 trillion and the industry is opening up hundreds of new opportunities for entrepreneurs. Right now, every healthcare practitioner is utilizing at least one mHealth application or medical tracking device to perform his or her duties faster and more efficiently. It won't be long until older technologies for patient monitoring and data gathering are replaced by healthcare apps with AI and machine learning functions. As they say, starting a business in the healthcare industry will require more preparation and bravery compared to venturing into other types of industries.

However, there is a discussion on whether new rules are necessary, as the legal framework might already be there under the bloc's General Data Protection Regulation (GDPR). The GDPR was adopted on April 2016 and took effect in May 2018. Facial recognition data is considered "biometric data", which is a special category of personal data resulting from the technical processing of physical, physiological, or behavioural characteristics. According to GDPR, the processing of "biometric data" to identify a person requires explicit consent from the person whose data is being collected. That excluded data used for national security, according to Diego Naranjo, an advocate at European Digital Rights (EDRi), a Brussels-based nonprofit.

Artificial intelligence is now being used to make decisions about lives, livelihoods, and interactions in the real world in ways that pose real risks to people. We were all skeptics once. Not that long ago, conventional wisdom held that machine intelligence showed great promise, but it was always just a few years away. Today there is absolute faith that the future has arrived. It's not that surprising with cars that (sometimes and under certain conditions) drive themselves and software that beats humans at games like chess and Go.

We've read plenty of stories of how AI can be horrible, but it can also be surprisingly useful. According to a report by the South China Morning Post, a person accused of murder was caught by an AI after he tried to scan his dead girlfriend's face to get a loan sanctioned. The report notes that a 29-year-old man in Fujian province was suspected of killing his girlfriend after an argument over finances. He tried to scan her face in a lending app called Money Station. The app uses AI to verify applications, and it asks them to wink during the approval process.

Recently, in cognizance of this seismic shift, the world's top AI researchers met in Asilomar, California to deliberate on AI principles and goals. In doing so, this eminent artificial intelligence society gifted humanity a framework of how to own the future. It is only by navigating AI ethical dilemmas, that we will avail the life saving technologies of applied artificial intelligence. The EU in its Responsible Research and Innovation initiative calls for investment in legal, social and ethics [LSE] research. Investment in LSE research will generate knowledge that can match artificial intelligence goals and society's needs.

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DESPITE HAVING SERIOUS problems with bias, raising enormous privacy concerns, and not actually being very reliable, businesses and services seem to be tripping over themselves to get on board the facial recognition train. The EU, it seems, plans to put some much needed brakes on this metaphorical choo-choo, and is planning to put strict limits on "the indiscriminate use of facial recognition technology" in order to protect European citizens. Documents seen by the Financial Times say the new legislation will "set a world-standard for AI regulations" with "clear, predictable and uniform rules… which adequately protect individuals." "AI applications can pose significant risks to fundamental rights," it continues. "Unregulated AI systems may take decisions affecting citizens without explanation, possibility of recourse or even a responsible interlocutor."

One of the largest annual legal tech conferences in the U.S. drew more attendees this year than ever, according to organizers, underscoring the dramatic growth of the legal tech industry and its increasing importance to the practice of law. The International Legal Technology Association's annual event this week at Disney World in Orlando, Fla., ILTACON, was on track to hit a total of 1,850 participants, up from 1,715 at last year's conference, which was held outside Washington. ILTACON is considered one of the premier legal technology gatherings of the year. The total in Orlando included 800 first-time attendees and exhibit booths from about 200 legal tech vendors. But the statistic that appeared seemed to energize top ILTA officials speaking to the press most, including ILTA CEO Joy Heath Rush, was that the conference has a growing international draw.

Yesterday, Waymo announced it would "open" a large dataset of self-driving training data. This gathered attention because Waymo has, by a huge margin, the largest number of self-driving miles under its belt, and thus one of the most envied collections of tagged data that can be used to train and test neural networks, one of the key tools used in building robots and self-driving cars. People setting up to build a self-driving car almost universally use machine learning techniques. With machine learning for computer vision, you provide the computer with images that a human being has already put labels on, saying what in the image is a car, or pedestrian, or road surface. Give the computer enough, and your machine learning technique -- today, most commonly a convolutional neural network -- will use advanced statistical techniques to come to a more general understanding of what distinguishes the various components.