Alan Turing Institute Data Science Lead: Data Ethics Self-Regulation Does Not Work
Ganna Pogrebna, Lead: Behavioral Data Science at The Alan Turing Institute, argues that data ethics must be regulated by law, if self-regulation will not work
Businesses have historically been left to self-regulate as they develop advanced data and analytics capabilities. But reports of data ethics violations in the media suggest this approach isn’t working that well.
In this episode of Data Conversations over Coffee, The Alan Turing Institute Lead: Behavioral Data Science Ganna Pogrebna says that the logical next step is to enshrine protections in law.
“At the moment, companies decide for themselves whatever they think is ethical and unethical, which is extremely dangerous,” she argues. “Self-regulation does not work.”
“In terms of how you address these issues, you need legal regulations in place,” she continues. “Unless we have the legal requirement for companies to abide by the law and do certain things, it is highly unlikely that they will engage in [ethical] behavior.”
Pogrebna goes on to say that using a ‘licensing' system to regulate the use of data in advanced algorithms is unlikely to work. Instead, she highlights some ideas about what data usage regulations could look like in the future.
These include expanding the Universal Declaration of Human Rights to include digital rights, and an idea known as ‘bottom-up trusts’. This idea, proposed by two academics in the UK, envisions organizations that would act as data custodians for members of the public.
Whatever form the laws take, Pogrebna believes that they are critical to ensure data security, even if it comes at the cost of inhibiting innovation.
“In Formula One, you know how to make a car very fast, but you need to make sure that it is safe for the driver and safe for everybody else around,” she concludes. “You need rules and regulations.”
Key Takeaways
- Take practical action on data ethics. There is a lot of debate around data ethics. But the key thing is to ensure that your organization is acting ethically
- Define your risk thresholds. Be sure to define the ethical ‘risk threshold’ beyond which your organization cannot proceed with a project
- The most important question is: ‘am I doing harm?’ Trust your internal barometer about whether your planned use of data is ethical