Why is global measurement important?

Tags
Responsible AI
Measurement
Data

On the importance of global measurements for key policy areas like responsible AI

Everything starts with a question

Every measurement begins with a simple question: What do we need to know? Whether it's the status of a project, the quality of a product, or progress on an initiative, measurements help us understand where we stand at a specific time and place.
When the information gathered is reliable, it gains the trust of a community with shared interests and values. This trustworthy data then serves multiple purposes, amplifying the initial reason for the measurement with each new use.


Measuring Progress in Key Policy Areas

Take, for example, the critical policy area of Artificial Intelligence (AI). As AI continues to be a hot topic globally, the international community has agreed that AI should be designed, deployed, used, and governed responsibly. Contributing to the realisation of this mission is the raison d’etre of the Global Center on AI Governance. Around the world, various principles and standards have been articulated for responsible AI, with the UNESCO Recommendation on the Ethics of Artificial Intelligence as the leading framework globally, having been adopted by 193 countries in 2021. 
This initial commitment marks the beginning of a collective journey that countries must navigate together, while also considering regional and national specificities. To ensure this commitment translates into real-world impact, it's crucial to measure and track the progress of responsible AI efforts worldwide. By doing so, we can see what actions countries are taking to honour their commitment and identify where support is needed to bridge gaps.

Why Measure Responsible AI?

If the idea of tracking this commitment isn't convincing enough, consider the various questions that such measurements can answer:
  • Which countries are leading the way in responsible AI?
  • Are there regional differences that need to be addressed in global discussions?
  • Which aspects of the commitment need more attention?
  • Are some countries excelling in certain areas while others struggle, and can we learn from each other’s experiences?
These questions highlight just a few reasons for measuring concepts like responsible AI. Different stakeholders, from policymakers to civil society organizations, global forums, and media outlets, can use these measurements in diverse ways to tackle AI challenges on different scales.

Agreements and Beyond Measurements

When discussing these topics, how we measure is as important as why we measure. The two are closely linked. The process of making a concept measurable involves breaking it down into dimensions and indicators and deciding what kind of data to collect and how. This process critically influences the results. Therefore, it’s essential to follow core values like rigour, fairness, and inclusivity at every step to ensure the final metric is reliable and meaningful.
One of the most challenging but valuable steps in global measurement is setting the benchmark: defining the ideal end stage for the countries being analyzed. This requires rigour, creativity, and openness, in order to be fair and reproducible. 
Setting this benchmark not only helps us understand why we measure but also unites us in working towards common goals. A well-crafted measurement can reinforce our collective efforts and guide us towards building a more equitable and sustainable future.

Author: Nicolás Grossman

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© Global Center on AI Governance copyright 2024

We're advancing local insights to create global impact on equitable AI governance through knowledge production and exchange.

© Global Center on AI Governance copyright 2024

We're advancing local insights to create global impact on equitable AI governance through knowledge production and exchange.

© Global Center on AI Governance copyright 2024