Once a common theme in science fiction movies and dystopian literature, artificial intelligence (AI) is usually portrayed as a convenient and practical technology.
However, it could have very serious ethical and moral implications, and even though current technology is still years away from achieving its full potential, there is already talk of how it will lead to enormous job losses with the looming redundancy of many human workers through the rise of computer automation.
Still, companies and people can benefit from the implementation of this new technology. There are already several applications available for demanding customers and money has been flowing into the sector: venture capitalists, hardware developers and other companies have significantly increased how much capital they dedicate to AI.
The industry is also not only being played by the usual suspects in the United States. China might become a serious contributor to the further development of the technology and its implementation in businesses.
In 2007, John McCarthy, from the Computer Department of Stanford University, described artificial intelligence as a science of creating intelligent machines and computer programs, especially using computers to understand human intelligence. He also described how the science could branch out to very specific parts that keep growing as humans increasingly grasp its potential.
Ten years later, AI is used with much more frequency and is slowly penetrating homes, especially in western countries. According to Narrative Science, 62% of companies and organisations will have adopted it by 2018. Also, the “care-bots”, devices that use artificial intelligence to answer the needs of the users, could reach a total value of $17.4bn by 2020.
It is estimated that, within the next five years, AI could also take over crucial parts of most businesses like marketing, customer service and sales. Traditional hardware firms clearly want a piece of the pie. According to iRunway, 2015 was an expansionist year for traditional hardware and software companies and their adventures into the AI world.
By 2015, Fujitsu had a total of 93 AI patents, while IBM had 88, NEC had 85 and Siemens and Microsoft both had 70. Venture capital funds have, therefore, anticipated major developments within the next few years, so have opened up their deep wallets. According to Venture Scanner, in the first six months of 2016, AI had already received a total of $974m in capital.
At the Top
The United States has traditionally been the leader in technology development. However, China is slowly starting to take on a similar role. Last October, President Obama sent out a “strategic plan” based on a simple assumption: the US is not the world leader when it comes to publishing academic research on deep learning, one of the branches of AI.
In fact, when the world’s leading AI researchers met last month in San Francisco for the annual meeting of the field, the number of Chinese research papers from Chinese researchers almost equalled the ones from the US.
The Chinese government seems to have also understood the potential of this technology. In the Five Year plan revealed in March of last year, the Chinese Government presented funding of this technological development as a great priority. Also, the Chinese tech giants have all created their own labs to develop AI.
More Than Hype?
AI has attracted interest from both tech insiders and venture capitalists but could it be just hype?
Facebook’s founder and CEO Mark Zuckerberg believes that AI has promise in the long run as it can help the company “identify risks that nobody would have flagged at all”, he wrote in his Facebook manifesto released on February 16th. He admitted the company, the largest social media entity in the world, is exploring ways to use AI to “tell the difference between news stories and terrorist propaganda”.
With computers getting more and more powerful, the deep learning capabilities of AI are also increasing. The software can be trained to recognise patterns in text, voice and images and act according to what they find.
Real Life Applications
Facebook’s algorithm is one of the many applications of AI. It tailors the content presented to the user based on the activity that user has on the social network. What people read on their newsfeed within the platform is based on what they like, share and read when they are engaged in the network.
There are, however, many applications of AI for companies beyond social media. Hedge funds are starting to adopt algorithms too, to decide where to invest their capital, as a means of providing investors with invesment opportunities with lower management fees. This increasingly popular “robot-advisory” is currently a buzz word within finance and could potentially disrupt finance as it takes away the human bias.
For this kind of investment advice, all the investor needs to do is answer questions about their risk preference and investment goals, and then the algorithm sets up the ideal portfolio for that client, which it manages every day.
Since 2015, the largest hedge fund in the world, Bridgewater Associates, has been developing PriOS, a software that, according to the Wall Street Journal, is supposed to manage the firm with the founder’s vision even when he is not around. This means that within three to five years, the software is supposed to be in charge of hiring and letting employees go as well as other management decisions.
The argument behind those shifts towards artificial decision-making lies in the belief that humans are too emotionally biased and take too long to decide on behalf of businesses. Automating all of these could possibly make things easier and more profitable for companies.
In trading, the adoption of AI has been prominent. There is no longer a need for traders to be selling and buying commodities using hand signals on Wall Street. The time for machines is here, and they are now mostly responsible for an increasingly big part of trading. Computers are supposed to improve liquidity and help pair up buying and sellers without a need for any intermediaries.
Also, some algorithms focus on different aspects of trading. They use AI to read and understand earnings statements, news from different media outlets and filings to have a better understanding of a stock – i.e., should it be bought or sold and at what price. But there has been some resistance regarding AI’s adoption in the field.
In 2012, a glitch in the system made Knight Capital lose more than $400m in only half an hour. After this and other problems, the regulators in the US implemented new rules for high-speed trading. One of them includes the requirement of a pause in trading for individual stocks if the price moves 10% or more in a period of five minutes.
half hour because of a system glitch
AI is believed to cut down the amount of administrative work, too. According to a report by Accenture, managers in 14 countries believe automation could be implemented to perform administrative tasks while humans would focus more on the creative side of the businesses and developing strategies.
In fact, AI is already being used to take care of legal bureaucracy. The start-up Lawbot uses AI to read contracts and assess which areas are potentially risky, and it also suggests how to improve the terms of the contract. The bot could be beneficial to law firms who deal with huge amounts of contracts and suggests the most relevant clauses for each case.
AI Going Mainstream
There are increasing concerns over the possibility of AI going mainstream. A study conducted in 2013 by the Oxford University estimated then that AI will be the cause for 47% of job displacement in the future. Another study by the OECD, conducted last year, estimated that 9% of jobs, will be displaced because of the technology just in the next two years.
of AI in the next two years
A survey conducted by Accenture showed that 84% of managers welcome the implementation of AI to help with the business.
Authorities don’t seem to be putting up any roadblocks in the near future either. The White House released a report on AI but didn’t advocate for any specific need for big regulations.
However, AI does raise concerns regarding its role in the world and society. For example, Tesla’s self-driving car, powered by AI, crashed and caused a fatality. Google’s AI app has labelled black people as gorillas. The problem with machine learning is that the company responsible for it cannot keep up with how much and what exactly it has learned until something unexpected happens.
in their businesses
It’s understandable that companies want to keep their secrets to themselves in a competitive business environment, but AI needs transparent algorithms in order to avoid situations like the ones mentioned above.
Luckily, the big players in the game seem to be heading in that direction. Apple paved the way with Siri, the personal assistant, but now the San Francisco-based company is seeing competition from Microsoft’s Cortana, Amazon’s Alexa and Google’s Personal Assistant.
Lately, there have been rumours that Apple might be joining the others at the “Partnership for AI” consortium. The goal of the organisation is to discuss the relationship between AI and the public as well as recommending what to do or not to do in the different areas of society where AI touches.