The Open Data Institute has launched its European Data and AI Policy Manifesto in order to advise policymakers ahead of the rollout of the EU AI Act.
That advice has a single purpose. To render the EU competitive in this new AI-dominated era, but without deviating from the values and policies that make it one of the world's greatest gatekeepers of citizen's wellbeing and rights.
But before getting into a it, a few words about the Open Data Institute or ODI for short. It's a UK-based non-profit research institute, but with an international perspective. It was founded in 2012 by Sir Tim Berners-Lee and Sir Nigel Shadbolt to share a vision for a world where data works for everyone.
The ODI is headquartered in London but has always been interested in policy globally, including in Europe, participating frequently in common working groups as well as releasing papers such as this.
This July's EU AI & Data Manifesto was designed to support policymakers and regulators as they navigate complex digital reforms, including the upcoming review of the EU’s digital acquis and the staged introduction of the EU AI Act.
The recommendations it makes revolve around rights, ethics, trust and innovation in relation to the EU's Commission will to incorporate Artificial Intelligence in its citizens' every day life, in the fabric of its society.
As the manifesto clearly states :
As the EU seeks to harness AI's immense potential to drive economic growth and address societal challenges, it must do so in a manner that protects citizens' rights, ensures fairness, and maintains public trust.
The manifesto breaks down the process of building a responsible and resilient data ecosystem in six principles:
- Strong data infrastructure
- Open data as a foundation
- Trust
- Trusted, independent organisations
- A diverse, equitable, and inclusive data ecosystem
- Data knowledge and skills
Let's take a brief look at the strongest advice each of those principle gives and when necessary infuse it with personal experience.
1. Strong data infrastructure
Among the recommendation there's one that stands out; the emphasis is on establishing a strong data governance infrastructure that:
ensures interoperability and that can support AI development while protecting citizens’ rights and European values
2. Open data as a foundation
The future is Open. Open data, open source. Quote:
The best possible foundation is open data, supported and sustained as data infrastructure. Only with this foundation will people, businesses and governments be able to realize the potential of data infrastructure across society and the economy.
Along openness, ODI suggest to also foster data altruism; organizations that voluntarily share data for the benefit of society.
May I also add the perspective of open source software, a matter that here at IProgrammer I have many times underlined?
From "EU Commission Reactivates Bug Bounties", State-sponsored bug bounty:
Open Source Software powers everything, from modern servers, to IoT, to the desktops at work and, as it seems, is at the heart of European Union systems too. While this EU bug bounty initiative is welcome, it is not something new. I covered the origins of the program in 2019, which emerged as part of the Free and Open Source Software Audit (FOSSA) project, thanks to Julia Reda MEP of the EU Pirate Party, who started the project thinking that enough is enough after severe vulnerabilities were discovered in key infrastructure components like OpenSSL. This prompted her to involve the EU Commission in contributing to the security of the Internet.
Then in 2024, in "Is The German State In Love With OSS?", we examined the German state launching openDesk for the "sovereign workplace":
openDesk, aims to become an alternative in the field of workplace software for the German Public Administration, under the ultimate motive of achieving digital sovereignty. Using openDesk, employees, IT administrators and public transport operators will have an effective open source based alternative in the workplace environment, therefore allowing the state to cut costs by not being held hostage in paying absurd amounts of fees to big corp software packages.
Last year the German state was again a driving force, as reported in "One State's Quest For Digital Sovereignty", aiming to move 30,000 PCs to LibreOffice:
With a cabinet decision to introduce the open-source software LibreOffice as a standard office solution across the board, the government has given the starting signal for the first step towards complete digital sovereignty for the country, with further steps to follow.
In other words, there's no digital sovereignty without open source and ensuring its security should involve state sponsorship.
3. Trust
For data to work for everyone, it needs to work across borders – geographic, organizational, economic, cultural, and political. There needs to be a participatory approach that empowers people to influence how data is used to serve society, the economy, and the environment. Open standards for managing digital identities and storing personal data for reuse also play an important role in the building trust.
4. Trusted, independent organisations
There needs to be a participatory approach that empowers people to influence how data is used to serve society, the economy, and the environment. As the manifesto sets it:
We recommend that the Commission and other bodies take decisive action to include diverse civil society voices in data and AI decision-making, reflecting the EU's focus on public services and accountability. This could involve ensuring diverse representation from civil society, academia, and industry on existing bodies' boards and advisory panels
5. A diverse, equitable and inclusive data ecosystem
Applying ethics and eradicating bias in the data are of quintessential importance.
For data to work for everyone, those collecting and using it need to be highly alert to inequalities, biases, and power asymmetries. Al organisations working in data must take proactive steps to ensure that they contribute fully and consciously to creating a diverse, equitable and inclusive data ecosystem
I've explored this subject quite a few times in the past. Back in 2019 and in How AI Discriminates, I looked into the "Survival of the Best Fit", an educational game developed by New York University that demonstrates practically how Machine Learning algorithms can make decisions based on bias taking as an example a fictional company's hiring process.
ML algorithms require data sets to be trained on. Turns out, the dataset used is too small for the algorithm to work, so you end up feeding it a commodity dataset used by a larger company such as Google, because Google can't go wrong, right?
Things pick up in pace significantly, until you get hit with complaints that some very qualified candidates have been rejected by the algorithm. Now you are tasked with answering "why", which it turns out is not easy to answer.
The complaints continue till the outcry is so big that you get sued for discriminating against Blueville residents in favor of Orangeville residents. It is an action that scares off the investors who retract their funding until finally you get shut down.
So what is the moral of the story? That algorithms are as good as the data they are fed and the more biased the data, the more biased the algorithm. Bias parameters can be demographic as in this case due to Google's fictional dataset including more applicants from Orangeville. This led the algorithm to infer that Orangevillers are more valuable than Bluevillers, thus the bias.
ODI in order to limit bias, inequality, and power imbalances, suggests broader access to data, infrastructure, and skills. It's vital that SMEs and start-ups, which are often excluded from large datasets, are supported through initiatives like AI Factories and their Data Labs referenced in the AI Continent Action Plan.
6. Data knowledge and skills
In this modern world, digital skills are key. But according to an overview of digital literacy in the EU, published by data.europa.eu:
More than 90% of jobs in Europe require basic digital knowledge alongside traditional skills like literacy and numeracy [but] 32% of Europeans still lack basic digital skills.
ODI focuses on developing high-level skills in data and AI, promoting general data and AI literacy across the population, and prioritizing inclusion and diversity, such that those using and making decisions about data and AI come from a range of backgrounds and experiences.
It is recommended that public awareness campaigns should be launched to improve the general understanding of data and AI's societal implications, as well as integrate data and AI literacy into educational curricula across all levels, from cradle to grave.
AI in schools is an area where EU has been left behind by countries like the US, who have started talking on incorporating AI literacy into their curriculums years ago, as we examined in Artificial Intelligence for K-12 back in 2019:
The AI for K-12 Initiative wants to kick-start the discussion on how to incorporate learning about AI in the United States school curriculum, ultimately leading to national guidelines.
The guidelines, will define what students should know about artificial intelligence, machine learning, and robotics., are modeled after the CSTA standards for computing education and address grade bands K-2, 3-5, 6-8, and 9-12, hence teaching about AI looks like is going to be considered at par with the rest of the core subjects such as Math's and English.
Professor David Touretzky, an AI researcher at Carnegie Mellon University who led the AI for K12 working group, stated:
We need to prepare our youth for the huge societal changes coming from technologies such as intelligent assistants and self-driving cars. At the same time, we should be encouraging students to pursue careers in these areas to help meet national workforce needs. China, the UK, and the EU are already implementing AI education plans.
Teaching digital skills is one aspect, the other is to teach ethics in order to explain that while AI can bring benefits to society, at the same time it comes with then danger of it being misused, i.e. the biases that are potentially introduced.
Fortunately, there's initiatives that tackle that, like Hour of Code talking about AI when introducing computer science to kids. We've explored that in "Hour of Code Teaches AI For Good" and "AI for Oceans - Kids Use Computer Science For Good". Links at the end of the article.
At the end of the day, ODI's recommendations are wide-ranging, all-encompassing, thought-provoking and certainly invaluable in the EU Commission's drawing of policies for the future; for a competitive, inclusive and digitally sovereign European Union.
You can get hold of the full 13-page ODI manifesto, together with references to the aforementioned articles following the links below.
More Information
The ODI European Data and AI Policy Manifesto is available in full at:European Data and AI Policy Manifesto
ODI main website
Related Articles
EU Commission Reactivates Bug Bounties
Artificial Intelligence for K-12
Hour of Code Teaches AI For Good
AI for Oceans - Kids Use Computer Science For Good
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