Artificial intelligence has gained prominence recently due, in part, to big data, or the increase in speed, size, and variety of data that businesses are now collecting. Artificial intelligence, or AI, can perform data-related tasks with great efficiency, and it can identify patterns in the data that often eludes human analysis. As organizations strive to gain more insight from their data, it’s not surprising that the business world is looking to AI for a competitive edge.
It’s not like this is the latest and greatest innovation! The term artificial intelligence—an umbrella concept that encompasses everything from robotic process automation to actual robotics—was coined in 1955 by John McCarthy, an American computer scientist, and it gained traction in the academic community at the Dartmouth Conference the next summer. As Daniel Crevier describes it in his book Ai: The Tumultuous History of the Search for Artificial Intelligence:
In the summer of 1956, ten young scientists, some barely out of their doctoral studies, sat down to consider the astounding proposition that ”every aspect of learning or any other feature of intelligence can, in principle, be so precisely described that a machine can be made to simulate it.” Armed with their own enthusiasm, the excitement of the idea itself, and an infusion of government money, they predicted that the whole range of human intelligence would be programmable within their own lifetimes. Nearly half a century later, the field has grown exponentially – with mixed results.
By the early years of the 1980s, a consensus was forming that expert systems were the future of artificial intelligence. An expert system is a computer system that mimics the decision-making skills of a person. It makes sense in theory: feed enough data to the system to create the proficiency of a human expert, and you can theoretically get human-like decisions from it. Unfortunately, such systems are prohibitively expensive to develop and have only proven to be useful in targeted scenarios. In many respects AI has demonstrated a wide scope, but shallow influence: it has touched countless disciplines, but its impact has been limited to the most simple form of call-and-response interactions.
Today’s AI research and development focuses on artificial neural networks: systems duplicating the interconnected process of the human nervous system. AI can combine the reasoning ability of the human mind with the processing power of computers, such as in Apple’s Siri personal assistant and Amazon’s Alexa. A recent article in the Wall Street Journal stated, “Spending on AI technology is expected to grow to $47 billion in 2020 from a projected $8 billion this year, according to market-research firm IDC.”
As a consequence, some business executives are working to become familiar with methods of managing the development of applications and the design of algorithms across multiple lines of business. Brian Uzzi, a professor at Northwestern University’s Kellogg School of Management, has co-developed three AI courses for M.B.A.s. In April 2017, Kellogg plans to introduce Human and Machine Learning, a 10-week elective course. The broader objective, according to Mr. Uzzi, isn’t to create a cadre of engineer-executives, but to introduce future corporate leaders to the idea of making decisions with the help of machines. Artificial intelligence is now on the syllabus at top-tier business schools.
A recent MIT Technology Review looked at a major report from Stanford University, coauthored by more than twenty leaders in the fields of AI, computer science, and robotics and concluded that AI looks certain to upend huge aspects of everyday life, from employment and education to transportation and entertainment. The analysis is significant because public alarm over the impact of AI threatens to shape public policy and corporate decisions.
The report predicts that automated trucks, flying vehicles, and personal robots will be commonplace by 2030, but it cautions that remaining technical obstacles will limit them to certain niches. It also warns that the social and ethical implications of advances in AI, such as the potential of unemployment in certain areas and likely erosions of privacy driven by new forms of surveillance, will need to be open to discussion and debate.
In December 10, 2016, Andrew Tonner published the 9 Artificial Intelligence Stats That Will Blow You Away.
1.) Voice assistant software is the #1 AI app today: Many of these voice-powered AIs still leave something to be desired in terms of accuracy, and it was surprising that voice assistants outnumbered big data in overall popularity with businesses.
2.) AI bots will power 85% of customer service interactions by 2020: Bye-bye, call centers and wait times. According to researcher Gartner, AI bots will power 85% of all customer service interactions by the year 2020.
3.) Digital assistants will “know you” by 2018: Also from Gartner, digital customer assistants will be able to “mimic human conversations, with both listening and speaking, a sense of history, in-the-moment context, timing and tone, and the ability to respond, add to and continue with a thought or purpose at multiple occasions and places over time.”
4.) Amazon, Alphabet, IBM, and Microsoft to host 60% of AI platforms: These 4 tech giants already have significant cloud computing businesses, a trend researcher IDC sees as likely to continue and by the start of the next decade, will control most of the market for AI software applications.
5.) Get excited for self-driving cars: According to a study from leading consultancy McKinsey, the impact of self-driving cars will be tremendous, saving an estimated 300,000 lives per decade by reducing fatal traffic accidents. This is expected to save $190 billion in annual critical care and triage costs.
6.) 20% of business content will come from AIs by 2018: In a potentially apocalyptic turn for members of the media reading (or writing) this, AI-powered software will write as much as 20% of business content in a mere two years’ time according to Gartner.
7.) AI drives a $14-33 trillion economic impact: In a research report to its investors, Bank of America argued that the rise of AI will lead to cost reduction and new forms of growth that could amount to $14-$33 trillion annually, in what it calls “creative disruption impact,” and that’s just the tip of the iceberg in some experts’ view.
8.) Robots will be smarter than humans by 2029? According to Alphabet director of engineering Ray Kurzweil, machines will be smarter than us by 2029. Kruzweil doesn’t necessarily see this as being a negative, though. Among many other “bold” predictions about our AI-laden futures, he believes people will start living forever around the year 2029 as well. Whether that’s the result of some Matrix-like scenario coming to fruition isn’t immediately clear, but obviously leading experts in the field believe major changes to our social fabric are only a little more than a decade away.
9.) Zero people actually know how big an impact AI will have: While it’s certainly easy to get wrapped up in the litany of predictions, it’s perhaps most useful to simply keep in mind that AI should have a major economic impact from which investors can undoubtedly benefit from today.
The one concrete takeaway is that AI will contribute to the rapidly shifting technology landscape for our industry. Organizations that want to get or stay ahead will be flexible adapters who are willing to evolve their operations to take advantage of AI-based tools that enhance the customer experience, streamline internal processes, and feed the business pipeline.
Summary: Artificial intelligence (AI) is all around us – we encounter it in our daily tasks, such as talk-to-text and photo tagging, and it is contributing to cutting-edge innovations such as precision medicine, injury prediction, and autonomous cars. AI is the next big revolution in computing and holds the promise to provide insights previously unavailable while also solving the world’s biggest challenges.
About The Author
Roger Gudobba is passionate about the importance of quality data and its role in improving the mortgage process. He is an industry thought leader and chief executive officer at PROGRESS in Lending Association. Roger has over 30 years of mortgage experience and an active participant in the Mortgage Industry Standards Maintenance Organization (MISMO) for 17 years. He was a Mortgage Banking Technology All-Star in 2005. He was the recipient of Mortgage Technology Magazine’s Steve Fraser Visionary Award in 2004 and the Lasting Impact Award in 2008. Roger can be reached at email@example.com.