Mystified and vilified at the same time.
40% off TNW Conference!
In the past few years, advances indeep learning and artificial neural networkshave renewed interest in AI.
In 2018,more than 3,500 AI paperswere published in the arXiv preprint processor.
To put that in perspective, in 2008, the figure stood at 277.
And where innovation sprouts, money follows.
Consultancy firm PricewaterhouseCoopers estimates AI to be worth$15 trillion by 2030.
Under such circumstances, its natural for tech companies find all sorts of ways to leverage AI.
Survey aftersurveyshows that more and more companies implementing AI or planning to do it in some way.
But in manyif not mostcases, the approach to artificial intelligence is only in name.
(Interestingly Mallazzo points out in his article that VC firms are also complicit in mystifying AI.)
So its easy for marketers to get away with renaming old technology as AI.
Moreover, current AI models work in complicated ways that are oftendifficult to interpret even by their own creators.
The hype is also creating a growing demand for news stories and articles about artificial intelligence.
Tech publications often rush to report on the latest AI paper without bothering to understand the underlying technology.
Even mathematicians who should know better get caught up in the mystical haze andanthropomorphize AI.
A reality check on AI
The mystification of AI fully justifies the backlash by the science community.
I personally agree with most of the arguments in these articles.
First, we must recognize that artificial intelligence is a fluid term, whose definition changes with time.
Therefore, we need to define what is the current context of AI.
Can we consider anything that uses a machine learning algorithm as artificial intelligence?
Should AI be limited to systems that employ neural networks and deep learning algorithms?
If yes, what is the minimum level of cognitive accomplishment for a system to be considered AI?
But this might make things too complicated.
Therefore, we will still need the umbrella term artificial intelligence to describe the space in general.
However, startups and research labs need to abandon practices that confuse their audience.
And heres my personal recommendation to writers and news organizations.
Given the current hype surrounding AI, theres nothing wrong with using artificial intelligence in headlines.
This will help readers develop a realistic picture of the capabilities and limits of current artificial intelligence technologies.
Articles such as Mallazzos are helpful, but vilifying the misuse of AI terminology is not enough.
There should also be efforts inmaking AI understandable to the less tech-savvy audience.
You shouldnt have a computer science degree to know that neural networks are not magic.
In the past seven decades, overpromising and underdelivering by scientists and researchers triggered AI winters at different stages.
Protecting AI from another quasi-winter is a collective duty that requires responsible behavior from all the people involved.
Like them onFacebookhere and follow them onTwitter.
