Bias and ethics in artificial intelligence have captured the attention of the public and some organizations following some high-profile examples of it at work. For instance, there has been work that has demonstrated bias against darker skinned and female individuals in face recognition technology and a secret AI recruiting tool at Amazon that showed bias against women, among many other examples. But when it comes to looking inside at our own houses -- or businesses -- we may not be very far along in prioritizing AI ethics or taking measures to mitigate bias in algorithms. According to a new report from FICO, a global analytics software firm, 65% of C-level analytics and data executives surveyed said that their company cannot explain how specific AI model decisions or predictions are made, and 73% have struggled to get broader executive support for prioritizing AI ethics and responsible AI practices. Only 20% actively monitor their models in production for fairness and ethics.

Artificial intelligence is cast all at once as the technology that will save the world and end it. To cut through the noise and hype, VentureBeat spoke with luminaries whose views on the right way to do AI have been informed by years of working with some of the biggest tech and industry companies on the planet. Below find insights from Google Brain cofounder Andrew Ng, Cloudera general manager of ML and Fast Forward Labs founder Hilary Mason, Facebook AI Research founder Yann LeCun, and Accenture's responsible AI global lead Dr. Rumman Chowdhury. We wanted to get a sense of what they saw as the key milestones of 2018 and hear what they think is in store for 2019. Amid a recap of the year and predictions for the future, some said they were encouraged to be hearing fewer Terminator AI apocalypse scenarios, as more people understand what AI can and cannot do.

Given the speed of innovation in the digital realm, it's exciting to see our partner Cloudera continue to stay ahead of the game with their recent acquisition of Fast Forward Labs (now known as Cloudera Fast Forward Labs), a top-tier applied research and advisory services company. Cloudera Fast Forward Labs, will concentrate on practical research into new approaches to data science and applying research to business problems that are broadly applicable to a variety of industries and applications.

Cloudera said today as part of its second-quarter earnings report that it is acquiring Fast Forward Labs, a startup that gives companies the latest information on how to apply machine learning and AI to their businesses, as well as consulting. The company's stock has weathered somewhat of a beating since it went public, though it was able to beat Wall Street's expectations today. But the more interesting news is the acquisition of Fast Forward Labs, a company that specializes in consulting with larger enterprises about emerging trends in machine learning that can help their businesses grow. Cloudera specializes in operating on top of open-source technology, looking to deliver an enterprise-grade product for larger organizations. "On the way, we built a profitable company with real impact on our clients' products and businesses. I'm proud of what we've accomplished," CEO and co-founder Hilary Mason said in a post announcing the acquisition.

"Boyfriend Maker," an app that allowed users to create and chat with a virtual "boyfriend" was at the top of the App store in Asian markets and was rated #1 in Japan, the Daily Dot had reported. The app used Artificial Intelligence that allowed it to learn language from its users. Within months, it was pulled from the app store when its chat responses became racist, sexist and sometimes even violent. "It was horrible," according to Hilary Mason, the CEO and founder of Fast Forward Labs. She spoke about the app at a media and tech conference recently to illustrate the point that much of the work humans have done around machine learning and artificial intelligence has been done outside the mainstream tech community.

Computer science has long been a discipline seemingly dominated by males, with the number of women in the field, and even of those graduating with technology degrees, perennially lagging behind the number of men. A recent study by the National Girls Collaborative Project in the United States and the success of conferences like "Women in Data" in the UK suggest that this may be beginning to change, and one catalyst for that change may be the burgeoning field of artificial intelligence (AI). Take Cylance, the fastest growing cyber-security software startup in the past ten years, according to research firm Gartner. The company developed an AI-based alternative to traditional antivirus (AV) -- and just recruited the second female member for its fast-growing data scientist team, now numbering 14. Another example of a company embracing women in the field of AI is Fast Forward Labs, an organisation that works with businesses to accelerate their data science and machine intelligence capabilities.

One of the main arguments the Israeli historian Yuval Noah Harari makes in Sapiens: A Brief History of Humankind is that humans differ from other species because we can cooperate flexibly in large numbers, united in cause and spirit not by anything real, but by the fictions of our collective imagination. Examples of these fictions include gods, nations, money, and human rights, which are supported by religions, political structures, trade networks, and legal institutions, respectively. As an entrepreneur, I'm increasingly appreciative of and fascinated by the power of collective fictions. Building a technology company is hard. Lost deals, fragile egos, impulsive choices, bugs in the code, missed deadlines, frantic sprints to deliver on customer requests, the doldrums of execution: Any number of things can temper the initial excitement of starting a new venture. Mission is another fiction required to keep a team united and driven when the proverbial shit hits the fan. While a strong, charismatic group of leaders is key to establishing and sustaining a company mission, companies don't exist in a vacuum -- they exist in a market, and they participate in the larger collective fictions of the zeitgeist in which they operate.

One of the main arguments the Israeli historian Yuval Noah Harari makes in Sapiens: A Brief History of Humankind is that mankind differs from other species because we can cooperate flexibly in large numbers, united in cause and spirit not by anything real, but by the fictions of our collective imagination. Examples of these fictions include gods, nations, money, and human rights, which are supported by religions, political structures, trade networks, and legal institutions, respectively. As an entrepreneur, I'm increasingly appreciative of and fascinated by the power of collective fictions. Building a technology company is hard. Lost deals, fragile egos, impulsive choices, bugs in the code, missed deadlines, frantic sprints to deliver on customer requests, the doldrums of execution, any number of things can temper the initial excitement of starting a new venture. Mission is another fiction required to keep a team united and driven when the proverbial shit hits the fan.

But how do you separate hype from reality? How can your company apply AI to solve real business problems in 2017? In September 2016, Luminary Labs convened 30 executives in healthcare, machine learning, and analytics for a grounded discussion on these questions with machine learning expert Hilary Mason, founder and CEO of Fast Forward Labs, and Sandy Allerheiligen, VP of data science and predictive and economic modeling at Merck. Here's a synopsis of what we discussed, and what AI learnings your business should keep in mind for 2017. AI and the Near Term 3 We've all seen the sensational headlines: The robots are coming, and they'll take our jobs! AI can do your job faster and more accurately than you can!

But how do you separate hype from reality? How can your company apply AI to solve real business problems in 2017? In September 2016, Luminary Labs convened 30 executives in healthcare, machine learning, and analytics for a grounded discussion on these questions with machine learning expert Hilary Mason, founder and CEO of Fast Forward Labs, and Sandy Allerheiligen, VP of data science and predictive and economic modeling at Merck. Here's a synopsis of what we discussed, and what AI learnings your business should keep in mind for 2017. AI and the Near Term 3 We've all seen the sensational headlines: The robots are coming, and they'll take our jobs! AI can do your job faster and more accurately than you can!