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'Artificial Intelligence: Our Savior Or Humanity's Final Invention?'

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'Artificial Intelligence: Our Savior Or Humanity's Final Invention?' Contents 3 5 7 15 22 26 | Artificial IntelligenceTitle of the document | • Artificial intelligence (AI) is a broad concept which has been around since the 1950s. Ever since the term caught on, the vague definition allowed for theoretical extremes to surface. Some, like Ray Kurzweil, foresee a limitless positive future. Others, like Stephen Hawking and Nick Bostrom, predict general artificial intelligence to be humanity’s last invention. • In this white paper we look at what artificial intelligence is and narrow this down to where we believe value lies. We then use a business model overlay to make a judgement about the potential for disruption. Artificial Intelligence | 4 | Artificial Intelligence Artificial intelligence is best summarized as boom, bust, boom, bust, boom. In order to avoid the next bust, it is crucially important to manage expectations. Narrow AI is here to stay, all other forms are likely still very far away. Artificial Intelligence | There are many different forms of artificial intelligence and the field of study is very broad. In the end, AI is all about statistics. We argue in this paper that focus should be on artificial narrow intelligence instead of artificial general - or super - intelligence. Narrow intelligence, which focuses on optimizing one specific task, is already being used today and advances in data and computing power in combination with a stronger focus on specific applications are important improvements in comparison with earlier AI boom periods. Within the artificial intelligence theme we focus mainly on developments in machine learning. The potential for this area to grow is very large, given the most recent advances in algorithms and data. Market size ranges from USD mid-teen-billions to USD one hundred and fifty billion by 2025. The vague definition of artificial intelligence leaves room to inflate estimates by means of including robotics or even parts of the car industry. We do not consider the exact size of the potential market to be of interest, we rather focus on how expectations are developing. Judging from that perspective it is clear that AI is hot again. An issue that emerged during past boom periods is that of timing. It has been proven to be very hard to make good predictions in terms of progress in AI. There is a large probability current predictions are wrong again. We draw the conclusion that, based on the required computing power and current data limits, it will become very hard to live up to the high expectations in the market currently. This statement should not be confused with downplaying the trend though. Narrow artificial intelligence is used today already and it is impacting the way we diagnose, interact and optimize. We believe in incremental progress from this base onwards. We do not believe in theoretical extremes, however, because the technical requirements for such scenarios are simply non-existent currently nor likely in the coming decade. We build on previous publications by Steef Bergakker that discuss the impact of business models on disruption and integration of new technology. Companies can be categorized as either value chains, value shops or value networks. We argue value chains will likely integrate artificial intelligence into their current processes in order to make these more efficient. Ocado, the online retailer in the UK, is a good example of this, as the company uses AI to optimize all of its logistics. Value shops on the other hand are the battlefield for AI. Value shops represent specialist goods and services. Often, AI solutions also provide these specialized products, such as translation services. Progress in natural language processing, for example, is a direct threat to today’s translation services. Many more examples of specialized services and goods can be thought of to be replaced by AI in the future. Whereas we argue AI to be sustaining innovation for value chains, we see it as potentially disruptive for value shops. The final business model, value networks, is the holy grail in terms of disruption potential and ‘winner takes all’ outcomes. Current networking companies, like Google, Facebook and Amazon, can integrate artificial intelligence into their current offering, but we think AI has potential to assist in the creation of new value networks, thereby potentially replacing the current ones. Artificial Intelligence Artificial intelligence is a hot topic again, just as it was twice before since the 1950s. But this time it is different…at least that’s what we are being told. What is not different from previous hype cycles though, are the discussions around theoretically extreme scenarios and the claim that this time it is different. Artificial Intelligence | In order to make a judgement about the current developments around artificial intelligence, it is important to compare definitions and to narrow these down to what we believe to be core trends. In this part we will discuss what artificial intelligence is, how it was formed throughout history, what we expect in terms of trends and whether this is indeed the end of humanity. We then take this discussion as a base for the next chapters where we discuss the market potential as well as a business model filtering approach. In 1956 a group of computer scientists came together at a conference organized by Dartmouth College. John McCarthy proposed “a research project on artificial intelligence”, which coined the term and described the project as follows: “an attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.” This is an extremely broad working description and it will not come as a surprise that this “summer” turned out to become several decades and the group of “carefully selected scientists” morphed into a new field of study within computer science and statistics that has attracted, and still attracts, thousands of researchers globally. A more formal definition of artificial intelligence is provided by J. Nilsson1, who defines it as: “that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment.” The interesting part of this definition is that it does not define intelligence as human intelligence per se. Given human intelligence is currently the natural choice, it can be used as a benchmark, but in certain areas benchmarking is done versus systems that exceed human intelligence already (like logistical scheduling and image recognition), at least in speed. Still, a definition like the one suggested by Nilsson leaves a lot of room for discussion and entails a wide variety of applications. Figure 1 shows a schematic for the field of artificial intelligence. Planning, robotics, natural language processing and many other disciplines can be classified under the AI umbrella. In this paper we will mostly focus on machine learning and narrow this down further to reinforcement learning where applications such as deep learning and neural networks are starting to develop. In essence, both those who proclaim AI to be the end of humanity and those who argue AI will provide us with the required tools to grow productivity and cure diseases, focus on machine learning as this is the main area with inherent disruptive capabilities. 1 The quest for artificial intelligence, 2010 Artificial Intelligence Figure 1 | Artificial intelligence classification Source: Nazre, Garg, 2015 The fields above can be separated into four tasks that define AI2. These are systems that think like humans (use neural networks and cognitive architectures), systems that act like humans (pass the Turing test3 through natural langue processing and social intelligence), systems that think rationally (optimization, deduction, reasoning and problem solving) and systems that act rationally (intelligent agents that use for example planning, learning, decision making). Replace ‘humans’ by ‘the most intelligent alternative’ and we can combined this line of thinking with Nilsson’s definition. Now that we know what AI is, we can discuss the different forms of AI, as there are plenty of those as well. Often, a separation is made between weak AI and strong AI, where strong refers to everything a human can do and weak, naturally, refers to specific tasks. Another, in our view better suited, specification of AI is the following: - Artificial narrow intelligence - Artificial general intelligence - Artificial super intelligence Narrow intelligence is used to optimize one certain task or specializes in one specific area. An example is playing chess, or arranging timelines on social media platforms according to your interests. General intelligence would match everything a human can do and super intelligence exceeds general intelligence in that it is superior to the most intelligent benchmark. General intelligence is often seen as the holy grail, super intelligence as the feared and unknown future, but we argue the focus from an investment perspective should be on artificial narrow intelligence. 2 Russell, Norvig, Artificial intelligence: a modern approach, 2009 3 The Turing test requires that a human cannot distinguish machine interaction from that of another human. Artificial Intelligence | Since AI is such a broad and vaguely defined topic, an “issue” emerges as observed by McCarthy. He argues that “as soon as it works, no one calls it AI anymore”. This can be clearly observed today as well. No one is discussing or arguing against the algorithms that define search engines like Google, suggest movies, series and music based on your search and purchasing history or virtual assistants like Siri (Apple), Alexa (Amazon) and Cortana (Microsoft). That is AI in its core, but the view of many people is blurred by Hollywood that has brought malicious robots, super-intelligence and other apocalyptic scenarios to the discussion.
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