A.I. Predictions for 2019
Artificial intelligence enjoyed a banner year in 2018. The underlying technology has developed to a point that AI is not just real – it’s useful, perhaps on its way to essential. The industry is buying into and furthering the hype as ideas that once seemed revolutionary are becoming ordinary. Each advancement means a new hyperbolic prediction rising in its place. Now Bernard Marr, noted author and futurist, has offered up his predictions in Forbes for where AI will go in 2019…and beyond.
The era of machines doing physical and “thinking work” is uncharted territory. Government is rightfully taking notice for a variety of reasons. Marr cites “the world’s two AI superpowers” – the US and China’s –– ongoing trade skirmishes as something to watch in the new year. He predicts that the ongoing back-and-forth will further the Chinese “[self-reliance]” push “when it comes to [AI] research and development.” He foresees growing nationalist tendencies having two effects: authoritarian governments will find AI attractive “to restrict freedoms, such as the rights to privacy or free speech”; and closing borders will jeopardize the “framework of open collaboration” that “has been instrumental to the rapid development and deployment of AI technology we see taking place today.” Further impediments will “slow the development of common standards around AI and data, which could greatly increase the usefulness of AI.”
Marr believes “an increased emphasis on measures designed to increase the transparency of AI” will continue in 2019. Public trust is vital for adoption, but businesses also stand to “benefit from openness which exposes bias in data or algorithms.” Technology like IBM’s AI OpenScale, which “gives real-time insights into not only what decisions are being made, but how they are being made” will become more normal (and vital) as consumers demand control over where and how their personal data is used by corporations.
If 2018 was the year people “[got] a firmer grip on the realities of what AI can and can’t do,” leading to improved applications of data-driven predictive technology, 2019 will be the year of businesses leveraging their improved understanding to “[move] from piloting and soft-launching to global deployment.” He predicts a “[branching] out” into new aspects of business, with “fit-for-purpose” tools being “increasingly…offered as-a-service,” as well as more businesses using data in conjunction with AI “to generate new revenue streams.”
Doomsday scenarios of an AI-fueled, workless dystopian future still garner their fair share of clickbait headlines, but data increasingly shows that near-term jobs lost will be outstripped by jobs created – Gartner “predicts that by the end of 2019…1.8 million jobs will be lost to automation” (mostly in manufacturing), with 2.3 million created, mostly in “education, healthcare, and the public sector.” This is because artificial intelligence is often best deployed as augmented intelligence – “something which can work alongside human professionals, assisting them with repetitive tasks while leaving the ‘final say’ to them.”
AI is now functional enough to be a regular part of our lives – in fact, many people already use it (think Siri or Alexa) without a second thought. Marr predicts that 2019 will see the continued rise of “services [that] will become increasingly useful as they learn to anticipate our behaviors better and understand our habits.” Data collection and analysis is “becoming increasingly streamlined and accessible,” and “AI assistants are designed to become increasingly efficient at understanding their human users.” That means better, more natural personal AI is on its way.
Even the most tuned-in pundits cannot predict the future. But if 2018’s growth is any indication, artificial intelligence appears set for another quantum leap forward in 2019 – and beyond.
The Investment and Financial Industry Faces the Same A.I.-Driven Evolution
Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generate trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.
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Contributor
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
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