As Fake News came into prominence during the 2016 American election and spilled like a massive tsunami into 2017, the tech giants did what they do best; throw technology at a problem. The bright and shiny sword they held forth was Artificial Intelligence (AI). Except it turned out to be dull and as useful as trying to mow the lawn with a hammer. And it’s unlikely it will any time soon.
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What AI is Good at and Bad at
The kind of AI that we see in Hollywood movies from Spielbergs more gentle take to the blunt force trauma of the Terminator is called “general AI” and is the kind that can carry on a diverse conversation, spot subtle clues and has nuance. It would, essentially, have a conscience. Except we don’t know what consciousness actually is. Today, AI has several branches, from Machine Learning to Natural Language Processing (NLP.) They’re all used in various ways and mixed and matched.
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Yet AI today can only do one thing very well. AI today is classified by techies as “weak AI” because it can’t really combine all the disciplines together to think. Keeping in mind that thinking is different from intelligence and different again from solving multiple complex problems.
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So AI is very good at doing a specific task that has a process to it. While AI can do some impressive problem solving, it solves problems within a set of confines.
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Why AI Can’t Solve Fake News
The primary challenge of I to deal with Fake News is that AI is today, unable to deal with nuance and subtlety. And Fake News is all about that. Over time, as in years, with extensive training, AI will likely improve. The challenge is that such training requires a lot of people and data to train the algorithms of AI. It also means a lot of energy and massive data centres. It may well be too expensive right now to train an AI and we’re also not in enough of an advanced state with understanding consciousness to bring AI along.
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This is further evidenced as both Facebook and Google backed away from using AI and have quietly added more humans to manage Fake News on their digital channels.
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For now, AI can’t solve this deeply complex problem. That means placing more onus on humans and using public policy tools to help deal with a form of propaganda that is sure to impact many countries in the years ahead.

About the Author webconomist

Giles is a globally experience marketing communications practitioner with over 20 years experience in the technology sector. He's brought a number of innovative technology products and services to market around the world. His work as a digital anthropologist is now over a decade of digital research understanding how consumers use technology. Giles is regularly interviewed by news media on digital topics. Currently he is managing partner of Ekspansiv, a consulting firm focusing on MarTech, SalesTech and Marketing Operations (MarOps). He's on the organising committee for the Atlantic Big Data Congress and co-founder/creator of the Ice Awards for creative in advertising. Giles has worked in senior management in both public and private companies and has been involved with 4 startups; three successful and one failed.

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