Sue Unerman
Jun 16, 2021

Are we mixing up magic and science (again)?

The industry's narrative around AI must not be allowed to drift into the magical, otherwise great harm could be done. We must, instead, guide AI ethically and responsibly, and design it to drive positive change

Are we mixing up magic and science (again)?

It’s always been true that people can manipulate data to fool others. (An index chart with a scale that starts at 50 not zero, for instance, is a classic and somewhat disappointing feature of some awards entries to exaggerate impact.) 

Now data may be manipulating us as AI takes control. 

The consequences of this are far reaching and profoundly dark. We should not believe in what we see without interrogation. For some, this has echoes of the pre-enlightenment mass belief in magic.  

Until the late 17th century, in the West, magic and science were pretty much the same thing. Sir Isaac Newton “discovered” gravity but he also worked hard to turn metal into gold with alchemy. Queen Elizabeth I sponsored the magician/mathematician Dr Dee who cast spells and taught Sir Francis Drake and Sir Walter Raleigh how to navigate the globe. Dee conversed with angels, and wrote algorithms (they aren’t anything new) to explain the solar system.

Magic fell from grace, as an endeavour for scholars and scientists in the enlightenment, replaced by cold, hard data. Today, one leading commentator on data science believes that we are in danger of thinking about it in terms that are magical.

R David Edelman is director at the Massachusetts Institute of Technology. A one-time advisor to former US President Barack Obama, he joined me at a keynote for NextM Austria – at a fascinating conference session, chaired by Omid Novidi, chief executive of MediaCom Austria.

Edelman pointed to one example of “magic” in tech: DeepFake (where machine learning and artificial intelligence is supercharging the ability to fake content)  – the fun aspect of which is compelling, the dark side of which is yet to be fully understood, or accounted for

Artificial intelligence is climbing up to the “Peak of Inflated Expectations”, according to the Gartner Hype Cycle (though nowhere near the “Plateau of Productivity”), but it is cropping up widely, and often usefully. Outside our industry, Edelman cited an education experiment where two years of progress was made in just six weeks as a result of personalised, AI-driven online learning programmes for schoolkids. AI is saving lives in screenings for breast cancer. 

For our industry, Edelman warns that AI is in its infancy. And there are dangers if we don’t guide AI ethically, responsibly and monitor its progress. 

Edelman suggests five key questions to ask when using AI. Crucially, this means asking specifically who designed it and whose reputation is damaged if it goes wrong. Many systems are designed for the current status quo by the current leaders of that status quo. Yet, simultaneously, we’re trying to change the status quo, to make our businesses stronger and better for the disruptions to come. 

As industry changemakers, we need to interrogate AI carefully. Can we on the one hand make pledges about being more inclusive in the work and in our management and, at the same time, allow AI to make decisions based on the biases of the past? 

One glance at the current situation shows that the status quo is not OK. The Economist has taken a look at how AI is working in Google Open Images and ImageNet. It found just 30-40% photos are of women (50% of the population, of course), that men are more likely to appear as skilled workers, and women in swimsuits or underwear.  Frequency of labels for men are high for “business, vehicle, management”. The equivalent for women includes “smile, toddlers, clothing”. 

Edelman reminded the conference audience of a key episode from America’s history – The Salem Witch Trials (pictured in a print by George H Walker, above) which took place in the 17th century in Edelman’s state of residence, Massachusetts. He warned that if we allow the narrative about AI to become magical, we are in danger of behaving like the residents of Salem, of becoming like uninformed credulous children and allowing unfair and even harmful practices to become the norm. We will fail to challenge the systems in a way that will create a better world.

In Salem, being an outsider was, at the minimum, harmful to your prospects of flourishing (most of the victims were misfits to a strict Puritan society). We need to actively design AI to encourage more diversity and bring in outsiders in our systems now. We must actively ensure that we design AI to drive change and difference.

Edelman says: “Don’t just build AI for performance, but also for opportunity, for justice and for inclusion.”

As WPP UK country manager and Group M CEO, Karen Blackett wrote in the foreword for our book Belonging: “Diversity is not a problem to fix. Diversity is the solution.”

When it comes to the development of revolutionary new systems and ways of working we all need to pay attention to ethics, to inclusion and belonging. 

Sue Unerman is chief transformation officer at MediaCom


Campaign UK

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