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“Algorithms are not biased; data is biased” – MWC 2019

Last week at MWC in Barcelona, the session panels focused on the hottest topics in mobile, such as 5G, artificial intelligence and blockchain. The more controversial panels discussed the bias found in data, and how that data goes onto inform algorithms, which results in unethical conclusions. Speakers and panelists pointed out the racial bias in prison sentencing, gender bias in mortgage loans, financial institutions, age-related bias that occurs during job recruitment, and pre-existing conditions in health care coverage.

Danny Guillory, the head of global diversity and inclusion at AutoDesk told Fortune Magazine that by running a search for a professional social network for social engineers, the results were primarily Caucasian men. Guillory pointed out that when you engage or ask for more results, the AI delivers candidates with similar attributes – more Caucasian men. Another example of AI bias is the notorious Microsoft’s Tay AI, when released on Twitter back in March of 2016, the AI quickly became misogynist and racist on social media within a staggering 24 hours.

AI may seem like an auxiliary technology to how we live our daily lives today, however, it will soon be the primary driver across the tech industry. PricewaterhouseCoopers estimates the world economy will reach an additional 15.7 trillion in value by 2030 due to artificial intelligence. To put this into perspective, the top 5 technology companies today have a combined value of about $4 trillion, which includes Apple, Amazon, Microsoft, Google and Facebook. The annual global technology spend is similar – about $3 trillion. Over the next decade, AI will drive a market 5x the size of tech’s current global spend.

Although this growth is exciting on many levels, the panelists at MWC 2019 voiced concerns about the handling of inherent biases that comes from data, as clearly discrimination by age, race, gender, education or other factors within audience segmentation is counterproductive to the advancement of society that AI promises.

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AI algorithms are responsible for making consequential decisions and are trained to find lookalikes or other markers to learn patterns. Some argue that the bias occurs when the computer system reflects the humans who designed it. Proven downsides to artificial intelligence have surfaced in recent years, for instance with fake news allegedly influenced the 2016 Presidential election. These accusations are proof that we have run out of time in addressing these concerns, especially as we near the precipice of a much larger, multi-trillion-dollar AI market.

Provided there is more diversity within the field of artificial intelligence, many of the panelists asked who should regulate the infractions of algorithmic bias – governments or markets? Many felt there should be an international community to establish guidelines for AI. But even then, will the lower classes be invited or what level of inclusivity will an international community realistically provide for, as the world’s most vulnerable and marginalized people are unlikely to be represented. In this way, AI could further the gap between lower class and upper class along socioeconomic lines, if it hasn’t done so already as AI is currently in use by the largest financial funds in capital markets.

The unanimous solution among the panelists and speakers was to broaden the conversation and not limit artificial intelligence jobs only to technical experts. “Requiring someone to know Python in order to work with AI is not democratizing AI,” one panelist pointed out. Along these lines, a more human centric approach is necessary.

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Beth KindigI’m an industry insider who writes free in-depth analysis on public tech companies. In the last 12 months, I predicted Facebook’s Q2 crash, Roku’s meteoric rise, Uber’s IPO flop, Zoom’s IPO success, Google’s revenue miss and more. Be industry-specific. Know more than the broader markets. Sign up now. I look forward to staying connected.

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  1. Joe Haluska Joe Haluska

    Wow! A lot to think about. In no particular order, some thoughts. Concerning the algorithms, “you get out of it what you put into it”, so if garbage in, then garbage out, and vice versa. So the construction is of paramount importance. Is AI simply subject to sampling error, hobbled by a Bayes Theorem type of restriction that makes decisions dependent on the “truths” to which it has access? And regarding regulation, IMO neither government nor markets, but rather an “United Nations” of academics, including technologists, ethicists, sociologists, psychologists……but does that lead to technological singularity? Does the AI eventually assume the responsibility of the managers?
    And then, is the bias itself in need of “self analysis”, attempting to correct its own errors? Does AI become the manager of humanity, for our own good, and hopefully not our detriment?
    Thank you Beth, for your as-usual leading edge report on the future…
    Regards, Joe


      These are great points, Joe! Garbage in, garbage out will def. apply to AI. I think the echo chambers with data are amplified with algorithms, and rather than AI competing with intelligent humans who have levels of complexity, it is simply spitting out patterns because it does not form intelligent thoughts based on emotional intelligence. I think AI will always be restricted to some level and will require humans to check the work that is being done.

  2. Richard Nilsson Richard Nilsson

    Let me pose on question that must be answered before any further debate is of any value to our understanding of the world around us:

    Maybe the data is biased because it reflects reality? Maybe equality is a myth and different groups perform at different levels at almost any task imaginable and also shows a great variation in their inclinations towards different behaviors?

    I don’t mean to be rude and I realize that this line of thought is anathema in Silicon Valley and that you are probably very aghast at how one could even ponder to say such things such obviously racist and fascist things, as I am saying now, but have you for instance read the debates concerning the heritability of intelligence among intelligence researchers or are you just trusting others who hold the same ideological biases as you to have given you the truth on the matter?

    In fact, there really is no serious debate among intelligence researchers that IQ, that is a proxy for the theoretic concept g, for generalized intelligence, is heritable by genetics, only how much of the variation between humans that can be explained by genetics. And there is a consensus on that a above average IQ is predictive of life income, educational attainment and propensity for criminality, for instance.

    Just as there is a consensus among climate researchers that we are undergoing climate change.

    Self-described liberals (I am not saying that you are one, but the culture of Silicon Valley can certainly be said to be one born of social liberalism) pride themselves on loving science (I do too) but unfortunately they are just as fast to deny the science that doesn’t fit their pre-conceived ideological notions as conservatives are when it comes to climate change, evolution and abortion.

    I hope that more people, certainly those with great power such as the ruling class in Silicon Valley, which arguably and very convincingly can be said to hold more societal power than any other group of industrialists ever did at any point in US history with their now totally unregulated and total grip on what can be discussed on what today is the public sphere, would try to examine their ideological premises and see if they align with the consensus of science, especially in these times of increased polarization.

    And this is not a defense of any ideology, we cannot derive ought from is, but a greater understanding of the world tends to produce better outcomes. For instance, if we acknowledge that people are inherently unequal and that that is through no fault of their own, we can perhaps create a more just and fair society where those born unlucky can be given much better conditions to live under than they have today where the myth that they are in some way to blame because they have not succeeded to the extent that others have goes to the dustbin of history. Just as those that think that homosexual is something one is born to be is more accepting of homosexuals, people probably would be more accepting of those that does not, for instance, have the cognitive tools to succeed in this increasingly complex world we live in.

    Due to AI we will soon have a great deal of the least intelligent members of society unemployed, and today’s societal regime, where Silicon Valley giants amass fortunes of hundreds of billions of dollars while those born unlucky have no prospects at all – they will not even be able to sell their labor for any prize, however low, because an AI solution will always be cheaper – could be changed into something more fair and just.

    Anyway, I really like your blog and podcast. Please keep up the good work.


      Hi Richard, Thanks for the reply. This conference was in Europe. It was held in Barcelona. I don’t think it comes from Silicon Valley or left/right wing United States politics. These are global data scientists who are concerned about the effects of data, and we should all listen as they have the most experience with this.

  3. Thanks for all the research paper it was very informative.!!

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