By Danilo Macedo, Head of Government Relations and Regulatory Affairs at IBM Brazil
We are in the age of Artificial Intelligence (AI). In fact, 84% of people in the world today use an AI-enabled device or service. As more people share their data to be leveraged by these systems, trust becomes the cornerstone of interactions with organizations. That trust manifests itself when the devices or services being used do what we expect them to do, in the same way that we learn to trust that a banking application will carry out accurate transactions.
However, it may vary how companies use our data or AI to provide us with multiple benefits, as well as the associated risks, because not all data is managed the same and not all AI technologies have the same process of creation. In this context, regulation is essential.
Regulating information management in the data economy
If data is like oil, we might say that, once refined, you get the gasoline of AI. It is this combination that can add value to individuals and companies in the data economy. However, there is one key element that still needs to be addressed in a meaningful way in regulatory frameworks: the different risks that data-driven business models pose to people.
At IBM, we believe there are two distinct categories of data-driven business models:
- the high risk that use people’s data as a source of income (external data monetization). In this model, people have little understanding of how their data is accessed, how it is used in the data economy, or the level of risk they take in providing it.
- the low risk ones that use the data to improve operations, products or services (internal data monetization). In general, people can hope that their data doesn’t come out of this list or they can vote with their wallet if they are not satisfied.
This distinction will allow us to seek more appropriate and balanced regulation. For example, you can adjust the regulatory burden to be commensurate with the risks of data-driven business models, increase transparency of data resale, require buyers to verify that data has been handled legally and transparently, among other obligations.
Precisely regulating Artificial Intelligence technologies
From an AI perspective, at IBM we believe that these systems should prioritize people’s privacy and the rights of data subjects. That’s why we’ve been calling for precise regulation of AI around the world, in order to establish stricter controls and policies in the end uses of the technology, where the risk of societal harm is much greater.
Along these lines, it is fundamental that the regulation around AI considers three principles: first, that a the purpose of AI is to enhance Human Intelligence, not replace it; second, that the data and knowledge generated by that data belong to its creator; and third, that powerful new technologies like AI must be transparent, explainable, and mitigate harmful and inappropriate biases.
Our call to action is clear: it is essential to build trust without stifling innovation, while also establishing safeguards in problematic use cases for change or correction. Other aspects to guide regulation around AI are:
- Demand transparency. Organizations need to be up front regarding when, where and how they are using AI and data. For example, if a person is talking to an AI-powered virtual assistant, they should be told that they are talking to the AI and not a live person.
- Propose different rules for different use cases. Policies should reflect distinctions between higher risk and lower risk applications. For example, the risks posed by a virtual assistant are not the same as with an autonomous vehicle.
The ways organizations use people’s data and AI are constantly evolving. It is not regarding prematurely implementing new data protection rules or banning technology because both are transversal axes of innovation. It’s regarding collaborating to address the risks of data monetization, promoting the responsible advancement of technology, and pushing the boundaries of innovation by pooling our collective resources and expertise to improve our collective and individual well-being.
At IBM, we are optimists. We believe that by applying science and innovation to real-world problems, we can create a better tomorrow. More sustainable, more equitable and safe.
IBM press office
Weber Shandwick
E-mail: [email protected]
