The tool to improve AI transparency has arrived: AI Registers

Transparency, explainability and trust are big and pressing topics in AI/ML today. Nobody wants to find themselves at the receiving end of a black AI box system that makes consequential decisions (e.g., about jobs, healthcare, citizenship, etc.), especially if those decision are unfair, biased, or just plainly not in our favor. And most organizations agree that consumer trust and confidence that AI is being used ethically and transparently are key to unlocking its true potential.

And while there are literally hundreds of documents describing and prescribing AI principles, frameworks and other good things, last year there was no practical tool that could help with implementing transparency. And this tool is AI registers…

The Cities of Helsinki and Amsterdam jointly announce the launch of their public AI registers. The two registers were developed in collaboration with Saidot.ai, a Finnish company which specializes in “bringing transparency to consumer services” and which, to the best of my knowledge, is the only vendor in this space.

The idea for the company grew from the personal frustration of its founder and CEO, Meeri Haataja, who was “seeing how important transparency of AI is for the future of each one of us, and not being able to find too many meaningful ways to act on it.”

What is an AI register?

The City of Helsinki defines it as “a window into the artificial intelligence systems used by the City”. The City of Amsterdam calls theirs The Algorithm Register and “an overview of the artificial intelligence systems and algorithms used by the City of Amsterdam.”

Image source: https://algoritmeregister.amsterdam.nl/en/ai-register/

Image source: https://ai.hel.fi/en/ai-register/

Both registers describe: 
•  where and how the cities are using AI/ML, 
•  how these applications impact citizens and their everyday lives, 
•  how they were built, 
•  which data and algorithms they use, 
•  what kinds of decisions and assumptions were made in the design, build and deployments of the apps, and 
•  which ethical principles were employed to mitigate biases and risks. 

The registers also include contact information, such as email addresses, phone numbers and persons or teams to contact for further inquiries or to provide feedback.

Image source: https://algoritmeregister.amsterdam.nl/en/reporting-issues-in-public-space/

The language in the AI registers is a clear and easy to understand, aimed at an average citizen without any technical background in AI/ML. (Some technical information is provided as well, and while it is limited, one could probably obtain more via the contact information mentioned above.)

Benefits of AI registers for governments and citizens

By disclosing the information behind their apps, the governments improve transparency and accountability around their use of AI. As per an Omdia 2020 survey of 145 enterprise end-users, 62% stated they were either concerned or extremely concerned about AI accountability, demonstrating the importance of tools such as AI Registers which can help address this. Or, as the City of Helsinki Chief Digital Officer Mikko Rusama says, “Without trust, there is no use for AI”. 

For citizens, AI registers help to increase AI/ML literacy. They promote citizens’ awareness, participation and public debate which is the cornerstone of democratic governments. They build trust by increasing transparency in how, where and why the governments use their data, tax payers’ money and new technologies such AI/ML.

Because ultimately what we all want is responsible AI that benefits all of us, that respects diversity and human rights, encourages human flourishing, sustains human agency, and promotes societal, economic and environmental sustainability.

Benefits of AI registers for AI teams

For AI teams, AI registers offer a mechanism to “standardize transparency across your AI portfolio”; a “searchable and archivable way to document the decisions and assumptions that were made in the process of developing, implementing, managing, and ultimately dismantling an algorithm”. 

This move towards transparency of the industry is also a step in the right direction towards implementation of AI regulation. It is no surprise that, as per the Omdia 2020 survey, both end-user and vendor respondents are united in their desire to see AI regulations in place. When asked if AI should be regulated, 65% of end-user respondents and 67% of vendor respondents said “yes”. While the devil is in the details of who should regulate AI and how, attitudes in the community indicate the AI ecosystem is primed to help regulators find a path.

Saidot continues to actively develop its platform. New features and directions it is considering include:

•  Integrating AI registers into their clients’ AI development processes which would help expand it beyond communications and into solution governance, solidifying accountability;
•  Using AI registers to capture citizen feedback early on in the design and ideation process, to confirm desirability and enable co-design and co-creation;
•  Facilitating information sharing between government organizations, for example, to help with vendor selection. (The registers disclose whether external vendors were engaged and who they are.)

And given the newly announced proposal by the European Commission on AI regulation, Saidot is now “working full speed with companies in those high risk sectors to help them start putting in place proper AI governance”, says the company CEO. It was a great win for Saidot “to see the Commission encourage public authorities to take into use public AI registers as part of their New Coordinated Plan for AI”, she continues.

Beyond government: Why you should adopt AI Register for your AI/ML and data science apps

Trust is not just a fundamental prerequisite for a government to exist. Trust is equally fundamental in business. The entire reason your organization exists is because of your customers, consumers, employees and partners. So whether you are just getting your feet wet with AI/ML or are running your whole business on the foundation of AI and machine learning, let’s follow Amsterdam’s and Helsinki’s examples — let’s document and make public/ share with employees and partners what we are using AI/ML and data science for and how. We’ll all benefit from this disclosure.