姓名：杨杰聪学号：16130120180
嵌牛导读：近些年，AI概念十分地火爆，到底是真的这是下一个投资热点以及计算机领域的一大新方向呢，还是M2存量过高引起的资本挤兑呢？
嵌牛鼻子：AI，投资。
嵌牛提问：你如何看待AI的发展，人们对AI的期望是否过高？
嵌牛正文：
中文版链接：http://36kr.com/p/5107269.html
There was a point when the term AIconjured thoughts of Terminator and murderbots that took over the world. Today,there’s a resurgence of the term, but times have changed. Now, for many people,the initial image is that of helpful appliances, friendly robots, self-drivingcars, wearables, and automated dog walkers. It seems sprinkling in the term AImakes many common things suddenly edgy or worthy of attention. But do we allmean the same thing? Is all AI tech created equally?
AI has become a buzzword in much thesame way “organic” took over supermarkets earlier this decade. There is aninherent value in AI, and it’s plastered everywhere because it sells, even ifoverusing the phrase clouds ourunderstanding of what we’re really buying into.
With artificial intelligence becomingmore prevalent in the lives of everyday people, “AI” has turned into acatch-all term. As a result, vendors can label their solutions “artificialintelligence” without providing context for how it’s being applied and why it’sso valuable.
Kids’ toys that talk to you, marketingtools that automate campaigns, chatbots that answer questions: they’re alltouted as AI, but is their technology really on the same playing field? Theseissues aren’t going away — and as it turns out, they’ve been around for longerthan you think.
Why buzzwords can sting
The idea that marketing buzzwords canskew public perception isn’t new. Let’s think back to about five years ago whenpeople started deciding between conventional and organic vegetables. Whenyou’re forced to compare and contrast several different brands that all claimto be organic, being a smart shopper isn’t always easy. To make an informeddecision, consumers had to rely on packaging that was often misleading andinaccurate, designed to appeal to a healthy audience. As we all know, thispattern caused some major issues, and the FDA eventually had to step in.
This is eerily similar to the challengescompanies face today when choosing the right AI solutions, and that consumersface when scouting out new devices. People recognize AI as a valuable andexciting technology, and it’s no surprise vendors would jump on the opportunityto use the term. But when it’s used to describe any product with the slightestbit of machine learning, self-improving algorithms, or even rules-based logic,that’s when there’s an issue. As this blanket term infiltrates the tech market,it becomes clear that our field has a label problem.
What’s particularly concerning is thisruns the risk of starting another “AI Winter.” When AI first started makingheadlines in the ’80s, the hype led people to believe computers were takingover the world. As a result, public perception around AI became largelypessimistic, and major funding cuts soon followed. Once again, AI hype isresurfacing and the term is loosely thrown around, which could mean we’reheaded down a similar path. People will inevitably be let down by somethingthat says it’s AI but can’t deliver — like a chatbot that does nothing morethan request a web form. These mislabeled products could mislead people tobelieve that AI is all hype with no real value, bringing AI progress to ascreeching halt.
In the past few weeks, this issue hasmade its way to the forefront. Gartner’s Sharon George penned the article “How to Tell When Vendors Are Hyping AI Capabilities,” whichdescribed the difference between classical machine learning and today’s deeplearning processes, and how marketers confuse the two.
As a marketer in the AI space myself,these challenges are all too real. Working for a customer care company thatcreates intelligent virtual assistants (IVAs), it’s my job to help customersunderstand what they’re buying, comprehend the AI behind our products, andrecognize the competitive difference the technology makes for them. But today’smarket is full of confusion. As a result, my job has grown to also helpcustomers understand the difference between AI as a technology and AI as amarketing term.
Will history repeat?
Advocating for regulation is a trickything. It worked when the FDA established rules on which products can and can’tuse the term “organic.” But I don’t think it’s the right course of action tomandate benchmarks on which products get to use the term “AI” –especiallybecause as the technologies at play evolve, so too will the sophistication oftheir AI algorithms. It’s not as easy as the organic problem.
Before market confusion becomes undoableand the actual value in the term AI is set to null, we in the tech industryneed to be better about policing ourselves — and doing it before someone elsedecides to. A good first step: taking the initiative to educate ourselves onthis technical vocabulary (the way many people started educating themselvesabout food) to inch our way closer to a common understanding of AI and thecriteria for using the term.
As educated marketers and technologyteams, we need to hold ourselves to a higher standard and provide more detailedinformation about what’s in the box. If a company doesn’t preemptively statewhat their technology does, it likely has something to hide. As an industry, weshouldn’t be afraid to call out those who skew the meaning of AI just for aseat at the table.
We need to act fast before loose labelsand flawed marketing cloud the public’s perception of artificial intelligence.At the most basic level, we need to agree that true AI applications get smarterand more accurate with exposure to data, and rely less and less on humanintervention over time.
Just as the “organic” label confusedconsumers in the past, we need to bring clarity to the AI market to guidebuyers down the right path. The abundance of AI-driven products isn’t lettingup, and issues of consumer ethics and responsibility will only grow. There’s abright future ahead for AI, and it’s up to us to communicate its value in themost accurate and meaningful way possible.