12 Days of Christmas - Day 5: Knowledge

Data Research and Reports

There are many analytics experts and thinkers providing their perspectives on key issues in analytics or providing the outcome of research that will help our understanding to approach to move forward in analytics. Perfect for a Saturday deep read.

We found the following interesting:

From Atlantic Council: "The data divide: How emerging technology and its stakeholders can influence the fourth industrial revolution"

The data divide is the gap that exists between individuals who have access, agency, and control with respect to data and can reap the most benefits from data driven technologies, and those who do not. The data divide can only be reduced if the there is optimization in the data process, monitoring and evaluation of the policies and programs from major stakeholders, and alignment of public private partnerships for social good.

Key steps in closing the data divide include:

• understanding who or what is not represented in legacy datasets or during data generation to ensure mitigation of bias in ML/AI training datasets;
• recording data provenance that confirms authenticity of the data and builds trust and credibility in the reproducibility of the results from ML/AI training sets;
• requiring balanced statistical representation in the datasets used in modeling processes, to reduce ML/AI statistical bias; and
• ensuring ethical data stewardship for access and privacy concerns in ML/AI-based data operations.

Three stakeholder groups—private-sector firms, governments, and civil-society organizations— have important roles to play vis-à-vis the data divide.

• Private-sector firms capture and process copious amounts of data that are both valuable for their shareholders and socially valuable. When private-sector firms consider the needs of stakeholders aside from their shareholders, these data can be shared with governments and civil-society organizations, and used for social good.
• Governments have a dual role as the sole arbiters of data policy, as well as being major data capturers and processors. Policies that incentivize corporations to share socially valuable data, practices that make government-owned data more readily available, and efforts to reduce bias in government-collected datasets are all ways that the government can contribute to bridging the data divide.
• Civil-society organizations of all types have a key role to play regarding the data divide. They can train a new, more inclusive generation of data professionals, create new data-governance structures, and advocate for legislation that will positively affect the distribution of access and control over data across society.

From The Brookings Institution: "The EU AI Act will have global impact, but a limited Brussels Effect"

The European Union’s (EU) AI Act (AIA) aspires to establish the first comprehensive regulatory scheme for artificial intelligence, but its impact will not stop at the EU’s borders. In fact, some EU policymakers believe it is a critical goal of the AIA to set a worldwide standard, so much so that some refer to a race to regulate AI. This framing implies that not only is there value in regulating AI systems, but that being among the first major governments to do so will have broad global impact to the benefit of the EU—often referred to as the “Brussels Effect.” Yet, while some components of the AIA will have important effects on global markets, Europe alone will not be setting a comprehensive new international standard for AI.

The extraterritorial impact of the AIA will vary widely between sectors and applications, but individually examining the key provisions of the AIA offers insight into the extent of a Brussels effect that can be expected. Considering three core provisions of the AIA reveals that:

1. AI systems in regulated products will be significantly affected around the world, demonstrating a clear Brussels effect, although this will be highly mediated by existing markets, international standards bodies, and foreign governments.
2. High-risk AI systems for human services will be highly influenced if they are built into online or otherwise internationally interconnected platforms, but many AI systems that are more localized or individualized will not be significantly affected.
3. Transparency requirements for AI that interacts with humans, such as chatbots and emotion detection systems, will lead to global disclosure on most websites and apps.

Overall, this analysis suggests more limited global impact from the AIA than is presented by EU policymakers. While the AIA will contribute to the EU’s already significant global influence over some online platforms, it may otherwise only moderately shape international regulation. Considering this, the EU should focus on a more collaborative approach in order to bring other governments along with its perspective on AI governance.