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While still in its infancy, artificial intelligence (AI) has shown to be both a positive, beneficial solution to many areas of life and industry, as well as a potentially dangerous road to continue going down on. As tech companies, i.e. Google, continue to invest big dollars into developing and researching artificial intelligence, which is evidently going to - and already has - alter(ed) the way human beings live and interact with the world, the most important and not entirely answerable questions are: How will AI continue to change our lives? and Will it be for the good or bad?
What we consider to be AI - robots, chatbots, and the like - really only started to come about in the mid-to-late 20th century. Neural networks, the brain-inspired AI tools behind most of today’s cutting-edge artificial intelligence, are based on a mathematical theory which dates back to Warren McCulloch and Walter Pitts’ 1943 paper: “A Logical Calculus of the Ideas Immanent in Nervous Activity” (DigitalTrends); their paper described how networks of artificial neurons can be made to perform logical functions.
In 1950, scientist Alan Turing introduced the “Turing Test”, a test that challenged whether a machine could ‘think’ - could it answer questions like a human being despite not being one? At the Dartmouth Conference in 1956, the field of AI was launched and the term "artificial intelligence" coined.
Backpropagation, sometimes abbreviated to “backprop,” is considered to be the single most important algorithm in the history of machine learning as it allows creators to train their networks to perform better by correcting them when they make mistakes; it was first proposed in 1969, although it only became a mainstream part of machine learning in the mid-1980s (DigitalTrends). Once the '90s came around, massive changes began to be undertaken in AI: significant demonstrations in machine learning, intelligent tutoring, case-based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games, and other topics (AITopics). During this time, Cynthia Breazeal at MIT designed KISMET, a robot head that could recognize and replicate human emotion, and IBM’s Deep Blue Computer beat Garry Kasparov, reigning world chess champion, in a game of chess. Similarly, in the late 2000s, IBM introduced Watson, a question-answering computer system that is able to answer questions posed in natural language. It went on to compete against the top two Jeopardy! Contestants and won first place. Nowadays, we see AI on an almost daily basis in our lives: in self-driving cars, autopilot mode on airplanes, spam filters in your email, plagiarism checkers on online homework assignments, and even on your phone in the form of Apple’s Siri - your own intelligent personal assistant.'
Why is AI Important?
In the past ten years, the topic of artificial intelligence (AI), also referred to as machine learning or deep learning, has taken up a large portion of the conversation at Silicon Valley dinner tables. The concept of artificial intelligence lies in that computer systems can be used to perform tasks that would normally require a human being to do them; these tasks can range from speech recognition and translation into different languages, to visual perception and even decision making (ArrkGroup). As a result, AI has the potential to simplify business practices, solve and predict important outcomes, and provide analysis of customer insights and data, which in turn will allow companies to serve their customers more effectively and efficiently, thereby increasing their profits.
While many scientists and tech leaders such as Elon Musk, Bill Gates, and Steve Wozniak, have concerns over automation, and Stephen Hawking himself has warned that “AI could lead to tragic unforeseen consequences” (Forbes, 1), several large and mid-level technology companies are still moving forward in creating their own AI software and integrating it into their businesses. Google, Facebook (who reportedly had to shut down an AI engine this past summer after developers discovered that the engine had created its own unique language (Forbes, 1)), Amazon, and Apple have continued to invest money into researching and developing their own AI.
So, if AI can do all these things and simplify our lives, what could possibly be so bad about it?
Well, a few things actually.
AI automation will likely increase the levels of unskilled unemployment. In the past few years, we’ve already seen ‘AI’ in the form of movie-theater kiosks and McDonald’s “Create Your Taste” kiosks – an automated touch-screen system that allows customers to create their own burgers without interacting with another human being (TheGuardian); who’s to say there won’t be hundreds of thousands of Lyft and Uber drivers who may end up losing their jobs to driverless cars one day (PandaSecurity)? Also, to keep one's AI program running can be quite costly, especially in terms of maintenance and repair; programs need to be updated to suit the changing requirements and machines need to be made smarter (Buzzle). While machines are able to automate themselves to repeat mindless tasks and can store copious amounts of data, we don’t know how well they can alter their responses in changing situations the way humans can. One of the most glaring cons to AI is its lack of emotion as well as its lack of creativity. Humans are creative thinkers who rely on touch and feel and world-experiences to cultivate their ideas and messages; AI is driven by programs and processes that lack these qualities (Buzzle). With an over-reliance on AI, our own intelligence and ability to problem-solve may start to suffer as well. Finally, the one con that tends to be over-dramatized in conversations on AI (and maybe rightfully so?), and is also depicted in nearly every robot movie ever released, is the instance in which AI falls into the wrong hands or is created by someone with malicious intent - there is potential that we may end up looking at worldwide chaos and disruption.
While the list of cons of AI can run quite long, there are several important positives to this growing field - and these are the reasons why companies such as Google (owned by parent company, Alphabet) are very driven in funding their own AI.
Humans cannot sift through all the datasets in Big Data, whereas AI “can chew through that data as fast as the Xeon processors in the servers can go and derive insights from the data much faster than any human could” (Datamation). AI helps make faster actions and decisions in areas like automated fraud, and AI processing is able to ensure error-free processing of data (while humans are more prone to errors). Additionally, while humans tend to get bored of mundane tasks, machine’s don’t, so AI can do repetitive, automated tasks and increase the productivity of resources, while humans can focus on more creative tasks instead (Datamation). Though AI still lacks basic emotions that only humans are capable of producing, AI can still serve a function as a “home” robot in helping seniors with everyday tasks and allowing them to stay independent and in their homes (BigData-MadeSimple). AI, through improved prediction, can help in achieving better outcomes in medical diagnosis, oil exploration, and demand forecasting. Because machines have more access to data than one person ever could (and they also store an incomparable number of statistics within them), “AI could one day identify trends and use that information to come up with solutions to the world’s biggest problems”, such as climate change (BigData-MadeSimple).
A top reason why Google, Amazon, Facebook and the like are flocking to AI is how effective it is at helping a company reach its goals, as well as its ability to make sense and analyze all the data in a way that will allow said company to serve its customers more efficiently. Companies like Amazon “have massively capitalized on the strength of AI to personalize their communications and marketing promotions for customers” (Forbes, 2). For example, based on customer’s’ past buying patterns, Amazon can recommend products—or even regular automated delivery— that customers frequently purchase (Forbes, 2). This kind of personalization power has never been seen before and who really knows where it can continue to go?
Why is AI Important to Google?
Earlier this year, at their i/O conference, Google CEO Sundar Pichai stated that Google’s next massive undertaking will be AI. For Google, an investment in AI allows it to: build smarter, better products (like Google Home and the new and improved Google Translate), attract tomorrow’s talented employees to the company, and have its own in-house AI software become the basis for machine learning everywhere.
For Google, the AI web page (https://ai.google/) allows people around the world to hop on the AI train - the train that’s parked in Google’s backyard that is. The Verge poignantly states, Google “wants to wield influence in the wider AI ecosystem and to do so has put together an impressive stack of machine learning tools — from software to servers — [which means] you can build an AI product from the ground up without ever leaving the Google playpen”. One of Google’s AI offerings, Tensorflow, was originally an in-house tool for the company’s engineers to design and train AI algorithms, but was made public in 2015; it’s used to create custom tools for a whole range of industries, from aerospace to bioengineering (TheVerge, 1).
As a result, Google keeps you in the ‘Google world', especially through its community forums, and so engineers begin to heavily rely on all things Google AI; at the end of the day, this is ultimately to Google's benefit, even if it makes it seem like all of the programs and information that its offering is to your benefit only - and is only done out of the kindness of its heart.
Besides building AI tools and programs, Google uses AI to improve its own products. On Youtube, Google uses deep learning to provide more useful video recommendations. By keeping users engaged on the platform, the ad dollars will keep flowing in (Forbes, 3).
The most well-known Google 'product', Google Search, now uses machine learning, while Google Maps Street View automatically recognizes signs (Recode, 1). Another feature that Google has been working on is using your camera as an input device; this “Lens” feature for its Assistant service will tell you information about what’s in front of your phone camera, such as what type of flower you’re looking at, information about the restaurant across the street, and so forth (Recode, 1).
Google and the Competition
While it may appear that Google is just a search engine, Google is actually a lot of things, which makes you wonder if even Google sometimes loses track of all its product offerings.
In 2014, Google’s Executive Chairman, Eric Schmidt, shared: “Many people think our main competition is Bing or Yahoo. But really, our biggest search competitor is Amazon.” And the main area of competition for these two companies is in product searches (SearchEngineland). The New York Times reported that in 2009, nearly a quarter of shoppers started research for an online purchase on a search engine like Google and 18 percent started on Amazon, and then by 2011, almost a third started on Amazon and just 13 percent on a search engine.
Amazon's foray into AI is exemplified by "The Amazon Echo"; released in June 2015, The Amazon Echo a hands-free speaker that users control with their voice, a direct rival to the Google Home (same concept, different company). ‘Alexa’, as the device is sometimes referred to, can play user’s music from Spotify and Apple Music, answer questions, read the news, report traffic and weather, and controls lights, TVs, and even garage doors.
The next competitor is Apple. While numbers seem to show that Google has nothing to worry about as “Android currently holds around 84.7% of the market, compared to Apple's 11.7%” (TelegraphUK), Apple’s constant push towards innovation keeps Google on its toes. However, where Apple began to inflict the most damage on Google was its support for ad blocking in iOS 9. As The Verge points out, “ad blockers arguably improve the user experience, especially on mobile devices, as they block content from loading”; however, the ads they block are from Google’s DoubleClick for Publishers and Google’s DoubleClick Ad Exchange, the web’s largest ad exchange, and thereby inflict damage to Google’s revenues. In the scope of AI, Apple has been quite silent up until July of this year when it released its “Apple Machine Learning Journal", a 'somewhat fancy blog' documenting data and insights from Apple's researchers (TheVerge, 2); and even then, Apple still has a lot of room to grow and catch up in the AI race - but it knows it's lagging.
Our last competitor is Facebook. Facebook and Google make up more than 50 percent of the overall mobile ad market combined (SearchEngineLand), with Google at 33% compared to Facebook’s measly 19%. comScore data shows that users spend over 43% of their digital media time in apps, which means fewer users are using search and the web - aka Google. And, unlike Apple who lags behind in AI development, Facebook is making progress by having acquired Ozlo, an artificial intelligence startup, to help Facebook Messenger build out a more elaborate virtual assistant for its users (Recode, 2). Facebook M, which launched back in April, is the company’s AI-powered assistant that lives inside Messenger; it gives suggestions to users based on the context of their conversations (TechCrunch). The AI-assistant can proactively remind users to save pieces of content like articles, videos or FB posts to check out later or share in message threads using the “Saved” extension (TechCrunch).
The role of AI in society and the way we perceive it, as well as the way we use it in our daily lives, has drastically changed and morphed in the past fifty years alone. What we know today is not what we may know tomorrow. As Google continues its research into AI, so do its competitors. Amazon is building a similar cloud-computing group for AI, Facebook and Twitter have created their own internal groups for AI, and even Microsoft has reorganized much of its operation around its existing machine learning work, creating its own new AI and research group (Wired). If Google wants to stay at the forefront of AI, then let the AI games begin.
AITopics. (n.d.). Retrieved from https://aitopics.org/misc/brief-history
Amazon, Apple, Google, and the monopolization of the American economy. (2015, October 06). Retrieved from https://theweek.com/articles/581376/amazon-apple-google-monopolization-american-economy
Artificial Intelligence (AI): Pros and Cons - Panda Security. (2017, August 17). Retrieved from http://www.pandasecurity.com/mediacenter/technology/artificial-intelligence-pros-cons/
Artificial Intelligence: The Advantages and Disadvantages. (n.d.). Retrieved from https://www.arrkgroup.com/thought-leadership/artificial-intelligence-the-advantages-and-disadvantages/
Bradley, T. (2017, July 31). Facebook AI Creates Its Own Language In Creepy Preview Of Our Potential Future. Retrieved from https://www.forbes.com/sites/tonybradley/2017/07/31/facebook-ai-creates-its-own-language-in-creepy-preview-of-our-potential-future/#164a8cf1292c [Referenced as (Forbes, 1)]
CLAIRE CAIN MILLER and STEPHANIE CLIFFORD. (2012, September 09). Google Struggles to Unseat Amazon as the Web’s Most Popular Mall. Retrieved from http://www.nytimes.com/2012/09/10/technology/google-shopping-competition-amazon-charging-retailers.html?_r=1&ref=technology
Competitive threats to Google, and what they mean for you. (2016, May 25). Retrieved from http://searchengineland.com/competitive-threats-google-means-249772
Dormehl, L. (2017, September 23). A history of artificial intelligence in 10 landmarks. Retrieved from https://www.digitaltrends.com/cool-tech/history-of-ai-milestones/
Marr, B. (2017, August 08). The Amazing Ways Google Uses Deep Learning AI. Retrieved from https://www.forbes.com/sites/bernardmarr/2017/08/08/the-amazing-ways-how-google-uses-deep-learning-ai/#57125b263204 [Referenced as (Forbes, 2)]
Matney, L. (2017, June 27). Facebook improves its AI Messenger assistant ‘M’ with new wits. Retrieved from https://techcrunch.com/2017/06/27/facebook-improves-its-ai-messenger-assistant-m-with-new-wits/
Metz, C. (2017, June 03). Google, Facebook, and Microsoft Are Remaking Themselves Around AI. Retrieved from https://www.wired.com/2016/11/google-facebook-microsoft-remaking-around-ai/
Narula, G. (2017, September 15). Everyday Examples of Artificial Intelligence and Machine Learning. Retrieved from https://www.techemergence.com/everyday-examples-of-ai/
Newman, D. (2017, September 22). Top 4 Digital Transformation Trends In High Tech Industries. Retrieved from https://www.forbes.com/sites/danielnewman/2017/09/22/top-4-digital-transformation-trends-in-high-tech-industries/#149ed0de4bd3 [Referenced as (Forbes, 3)]
Oak, M. (2016, September 02). Weighing in on the Pros and Cons of Artificial Intelligence. Retrieved from https://www.buzzle.com/articles/pros-and-cons-of-artificial-intelligence.html
Patrizio, A. (2016, July 07). Pros and Cons of Artificial Intelligence. Retrieved from http://www.datamation.com/applications/pros-and-cons-of-artificial-intelligence.html
Shewan, D. (2017, January 11). Robots will destroy our jobs – and we're not ready for it. Retrieved from https://www.theguardian.com/technology/2017/jan/11/robots-jobs-employees-artificial-intelligence
Townsend, T. (2017, May 17). Google I/O 2017: Everything important that Google announced today. Retrieved from https://www.recode.net/2017/5/17/15654076/google-io-biggest-announcements-keynote-highlights-2017 [Referenced as (Recode, 1)]
Vincent, J. (2017, July 19). Apple has started blogging to draw attention to its AI work. Retrieved from https://www.theverge.com/2017/7/19/15998284/apple-ai-machine-learning-blog-journal-research [Referenced as (The Verge, 2)]
Vincent, J. (2017, May 18). Google's latest platform play is artificial intelligence, and it's already winning. Retrieved from https://www.theverge.com/2017/5/18/15657256/google-ai-machine-learning-tensorflow-io-2017-platform-play [Referenced as (The Verge, 1)]
Wagner, K. (2017, July 31). Facebook acquired an AI startup to help Messenger build out its personal assistant. Retrieved from https://www.recode.net/2017/7/31/16071646/facebook-acquisition-ozlo-artificial-intelligence-ai-messenger-personal-assistant [Referenced as (Recode, 2)]
Williams, R. (2014, September 29). Why competition between Apple and Google is more brutal than ever. Retrieved from http://www.telegraph.co.uk/technology/google/11127694/Why-competition-between-Apple-and-Google-is-more-brutal-than-ever.html
The future of Artificial Intelligence: 6 ways it will impact everyday life. (2016, August 23). Retrieved from http://bigdata-madesimple.com/the-future-of-artificial-intelligence-6-ways-it-will-impact-everyday-life/