Answers.Body: <p>I think that by strict definition of the word inevitable, <strong>no, future AI Winter events are not inevitable.</strong> However likely or unlikely it may be, it is possible to control research spending and to create a more stable plan of funding research in Artificial Intelligence. Because it is <em>possible</em> to avoid an AI Winter event, an event is not <em>inevitable</em>.</p>
  
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Answers.Body: <p>Yes - there will always be Gartner Hype Cycles which leads to "AI Winters" - that is just a fact of human nature in large groups. There is no better evidence for "Hype Cycle" mentality than the stock market in how it reacts both high and low to whatever the hot item is. AI is much more susceptible to this given that AI tends to touch people in very real ways - will this technology become smarter than me? Will it replace me? Will it take over? Are we building new life? Who controls this? which for those that actually build or know something about these techniques and concepts would say that we are a very long way off it is even possible in the first place. To build systems that can at best maybe mimic the intelligence of a two year old we would consider it a major success. </p>
  
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Answers.Body: <p>The hype cycles are the rule these days, and AI is always a wonderful topic for unbelievable and crazy hype. I mean simple thing like speech recognition is still not working properly, but everybody is discussing how to survive the revolt of the terminator machines. So unless we can tune the hype down, the next AI winter is inevitable.</p>
  
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Answers.Body: <p>I would say an AI Winter has already happened in the 2000's when specialist systems were adopted in detriment of cognitive systems, neural networks for instance were poorly understood back then and because of that they got meager investments from large companies, Google was a notorious exception. Only some 3 or so years ago, with things like IBM Watson and driverless cars this field started to draw significant attention. And now I doubt it will be ignored again, the research has taken off from advanced PhD theses and becomes more and more widespread.</p>
  
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Body: <p>According to <a href="https://en.wikipedia.org/wiki/AI_winter" rel="nofollow noreferrer">Wikipedia</a> (citations omitted):</p>
  
  <blockquote>
    <p>In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later.</p>
  </blockquote>
  
  <p>The Wikipedia page discusses a bit about the <em>causes</em> of AI winters. I'm curious, however, whether it is possible to <em>stop</em> an AI Winter from occurring. I don't really like the misallocation of resources that are caused by over-investment followed by under-investment.</p>
  
  <p>One of the causes of the AI winter listed on that Wikipedia page is "hype":</p>
  
  <blockquote>
    <p>The AI winters can be partly understood as a sequence of over-inflated expectations and subsequent crash seen in stock-markets and exemplified by the railway mania and dotcom bubble. In a common pattern in the development of new technology (known as hype cycle), an event, typically a technological breakthrough, creates publicity which feeds on itself to create a "peak of inflated expectations" followed by a "trough of disillusionment". Since scientific and technological progress can't keep pace with the publicity-fueled increase in expectations among investors and other stakeholders, a crash must follow. AI technology seems to be no exception to this rule.</p>
  </blockquote>
  
  <p>And it seems that this paragraph indicates that <em>any</em> new technology will be stuck in this pattern of "inflated expectations" followed by disillusionment. </p>
  
  <p>So, are AI winters inevitable? Is it inevitable that AI technologies will always be overhyped in the future and that severe "corrections" will always occur? Or can there a way to manage this hype cycle to stop severe increases/decreases in funding?</p>
  
Tags: <history><social><ai-winter>
Title: Are AI winters inevitable?
UserDisplayName: Left SE On 10_6_19
ThreadText: # Are AI winters inevitable?
  
  (Asked by: username_0 on 2017-03-10)
  
  According to [Wikipedia](https://en.wikipedia.org/wiki/AI_winter) (citations omitted):
  
  > In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The term was coined by analogy to the idea of a nuclear winter. The field has experienced several hype cycles, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later.
  
  The Wikipedia page discusses a bit about the *causes* of AI winters. I'm curious, however, whether it is possible to *stop* an AI Winter from occurring. I don't really like the misallocation of resources that are caused by over-investment followed by under-investment.
  
  One of the causes of the AI winter listed on that Wikipedia page is "hype":
  
  > The AI winters can be partly understood as a sequence of over-inflated expectations and subsequent crash seen in stock-markets and exemplified by the railway mania and dotcom bubble. In a common pattern in the development of new technology (known as hype cycle), an event, typically a technological breakthrough, creates publicity which feeds on itself to create a "peak of inflated expectations" followed by a "trough of disillusionment". Since scientific and technological progress can't keep pace with the publicity-fueled increase in expectations among investors and other stakeholders, a crash must follow. AI technology seems to be no exception to this rule.
  
  And it seems that this paragraph indicates that *any* new technology will be stuck in this pattern of "inflated expectations" followed by disillusionment.
  
  So, are AI winters inevitable? Is it inevitable that AI technologies will always be overhyped in the future and that severe "corrections" will always occur? Or can there a way to manage this hype cycle to stop severe increases/decreases in funding?
  
  **Tags:** history, social, ai-winter
  
  
  ---
  
  ## 4 answers
  
  ### Answer by username_1 on 2017-03-10. Score: 1 | Accepted answer
  
  I think that by strict definition of the word inevitable, **no, future AI Winter events are not inevitable.** However likely or unlikely it may be, it is possible to control research spending and to create a more stable plan of funding research in Artificial Intelligence. Because it is *possible* to avoid an AI Winter event, an event is not *inevitable*.
  
  
  ---
  
  ### Answer by username_2 on 2017-03-14. Score: 1
  
  Yes - there will always be Gartner Hype Cycles which leads to "AI Winters" - that is just a fact of human nature in large groups. There is no better evidence for "Hype Cycle" mentality than the stock market in how it reacts both high and low to whatever the hot item is. AI is much more susceptible to this given that AI tends to touch people in very real ways - will this technology become smarter than me? Will it replace me? Will it take over? Are we building new life? Who controls this? which for those that actually build or know something about these techniques and concepts would say that we are a very long way off it is even possible in the first place. To build systems that can at best maybe mimic the intelligence of a two year old we would consider it a major success.
  
  
  ---
  
  ### Answer by username_3 on 2017-03-11. Score: 0
  
  The hype cycles are the rule these days, and AI is always a wonderful topic for unbelievable and crazy hype. I mean simple thing like speech recognition is still not working properly, but everybody is discussing how to survive the revolt of the terminator machines. So unless we can tune the hype down, the next AI winter is inevitable.
  
  
  ---
  
  ### Answer by username_4 on 2017-03-14. Score: 0
  
  I would say an AI Winter has already happened in the 2000's when specialist systems were adopted in detriment of cognitive systems, neural networks for instance were poorly understood back then and because of that they got meager investments from large companies, Google was a notorious exception. Only some 3 or so years ago, with things like IBM Watson and driverless cars this field started to draw significant attention. And now I doubt it will be ignored again, the research has taken off from advanced PhD theses and becomes more and more widespread.
  
  
  ---
  
  