Algorithms power transformative technology but also present many threats to users — which raises the question of how to prevent and regulate against potential disaster.

For technology users, particularly social media users, 2018 has been a year of awakening. The media began scratching the surface of the dangers of social media with the story of Russian parties influencing the U.S. election. Soon after, a slew of reports followed with details of how Cambridge Analytica used social media data to influence votes in both the United Kingdom and the United States. People were suddenly exposed to the dangers of how easily social media and the algorithms underpinning social platforms can be used to influence other users, and we’re now seeing how widespread the practice has become. Harmless, everyday actions performed by millions of users, such as taking fun surveys, had suddenly become tools for unscrupulous data miners.

The investigation into the Cambridge Analytica scandal was a high point for awareness of privacy breaches in the social media community, but it certainly was not the first. In February 2018, Guillaume Chaslot, a former YouTube employee, went public with his study on YouTube’s algorithms, which found extreme bias in relation to the 2016 election. The study found that 84% of videos recommended by the algorithm were pro-Trump, with only 16% pro-Clinton. Meanwhile, Twitter came under attack as a documentary by Project Veritas purportedly proved political bias in its regulation of its users.

The push for better regulation with regard to how algorithms work and how to protect user privacy has already advanced, with the European Union’s General Data Protection Regulation (GDPR) governing online data privacy and use of user data having gone into effect in May 2018. However, we contend that while these efforts have been aimed at regulating user data, efforts must be made to regulate algorithms themselves.

Algorithms Are More Than Just Social Media

The truth is, algorithms pervade our lives. They have existed in the systems that run and regulate our lives for decades, performing tasks from a national security early warning system to traffic control systems. More recently, algorithms have found their way into our cars, our homes, and now have tasks as varied as deciding how suitable we are as job candidates or helping to identify health issues.

As with social media, while these algorithms have delivered convenience and usability, they have also failed us.

3 Comments On: Coming to Grips With Dangerous Algorithms

  • Venets Media | September 22, 2018

    Great Article Thanks For The Information

  • Chandra Pandey | October 19, 2018

    In assessment of context, AI by design is pre action oriented & is a presumptive algorithm, therefore in default design is inclined to subjective & objective biases which often is against the consumer charter of neutral choices. In unrestricted & not well calibrated, regulated, governed rollout, it’s unfortunate & unaccountable contribution from software world of being automated propagator of biases at scale. Human action footprint can be bettered easily, quickly & with limited impact, black box complex algorithms & data points can only be bettered by redesigning processes & data collection as quarterly exercises.

    The time has come that there is debate & dialogue for open algorithm, governance for public scrutiny & disclosures for fixing the trust issues as the toxic genie is out of the bottle without default safeguards.

    Disclaimer: The views and opinions expressed are personal in nature and does not reflect the official policy or position of any organization.

  • Robert Jones | October 19, 2018

    This is a horse and barn door issue. The proliferation of algorithms knows no bounds. While it is, in theory, possible to create ethical guidelines for the development and application of algorithms, the idea of regulation and/or enforcement is most likely tantamount to science fiction. The negative effect of algorithms is much like cockroaches on restaurant row at this point. A good day is when there’s no evidence of them in day-to-day operations. Unfortunately, visible evidence is the only way to tell when they’re not staying in their place. We might have guessed that the things we invent and design will produce unmistakably human outcomes at some point. Technology will never be exempt from that inevitability. We’re only recently coming to realize that the fewer things we invent, the better off we’ll be.

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