Are we mixing up magic and science (again)?
It’s always been true that people can manipulate data to fool others. (A 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 seventeenth century in the west the magic and science were pretty much the same thing. Isaac Newton “discovered” gravity but he also worked hard to turn metal into gold with alchemy. Queen Elizabeth 1 sponsored the magician/mathematician Dr Dee who cast spells and also taught Drake and 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 endeavor 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.
- David Edelman is director at the Massachusetts Institute of Technology. A one time advisor to Barack Obama he joined me at a keynote for NextM Austria – at a fascinating conference session chaired by Omid Novidi, ceo 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 (AI) 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 of our industry Edelman cited an education experiment where 2 years of progress was made in just 6 weeks as a result of personalized 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 advises 5 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. They 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 include “smile, toddlers, clothing”.
Edelman reminded the conference audience of a key episode from America’s history The Salem Witch Trials took place in the seventeenth century in Edelman’s county of residence Massachusetts. He warned that if we allow the narrative about AI to become magical then 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 which will create a better world. In Salem being an outsider was harmful at the minimum 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.
This entry was posted
on Friday, June 25th, 2021 at 6:05 pm and is filed under MediaComment.
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Responses are currently closed, but you can trackback from your own site.
Do you believe in data magic?
Are we mixing up magic and science (again)?
It’s always been true that people can manipulate data to fool others. (A 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 seventeenth century in the west the magic and science were pretty much the same thing. Isaac Newton “discovered” gravity but he also worked hard to turn metal into gold with alchemy. Queen Elizabeth 1 sponsored the magician/mathematician Dr Dee who cast spells and also taught Drake and 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 endeavor 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.
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 (AI) 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 of our industry Edelman cited an education experiment where 2 years of progress was made in just 6 weeks as a result of personalized 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 advises 5 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. They 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 include “smile, toddlers, clothing”.
Edelman reminded the conference audience of a key episode from America’s history The Salem Witch Trials took place in the seventeenth century in Edelman’s county of residence Massachusetts. He warned that if we allow the narrative about AI to become magical then 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 which will create a better world. In Salem being an outsider was harmful at the minimum 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.
This entry was posted on Friday, June 25th, 2021 at 6:05 pm and is filed under MediaComment. You can follow any responses to this entry through the RSS 2.0 feed. Responses are currently closed, but you can trackback from your own site.