Creating Real Value: Skills Data in Learning and Employment Records

Curated on Posted on by Stefaan Verhulst

Article by Nora Heffernan: “Over the last few months, I’ve asked the same question to corporate leaders from human resources, talent acquisition, learning and development, and management backgrounds. The question is this:

What kind of data needs to be included in learning and employment records to be of greatest value to you in your role and to your organization?

By data, I’m talking about credential attainment, employment history, and, emphatically, verified skills data: showing at an individual level what a candidate or employee knows and is able to do.

The answer varies slightly by industry and position, but unanimously, the employers I’ve talked to would find the greatest value in utilizing learning and employment records that include verified skills data. There is no equivocation.

And as the national conversation about skills-first talent management continues to ramp up, with half of companies indicating they plan to eliminate degree requirements for some jobs in the next year, the call for verified skill data will only get louder. Employers value skills data for multiple reasons…(More)”.

Name Your Industry—or Else!

Curated on Posted on by Stefaan Verhulst

Essay by Sarah M. Brownsberger on “The dehumanizing way economics data describes us”: “…My alma mater wants to know what industry I belong to. In a wash of good feeling after seeing old friends, I have gone to the school website to update my contact information. Name and address, easy, marital status, well and good—but next comes a drop-down menu asking for my “industry.”

In my surprise, I have an impulse to type “Where the bee sucks, there suck I!” But you can’t quote Shakespeare in a drop-down menu. You can only opt only for its options.

The school is certainly cutting-edge. Like a fashion item that you see once and assume is aberrant and then see ten times in a week, the word “industry” is all over town. Cryptocurrency is an industry. So are Elvis-themed marriages. Outdoor recreation is an industry. A brewery in my city hosts “Industry Night,” a happy hour “for those who work in the industry”—tapsters and servers.

Are we all in an industry? What happened to “occupation”?…(More)”.

Integrating Participatory Budgeting and Institutionalized Citizens’ Assemblies: A Community-Driven Perspective

Curated on Posted on by Stefaan Verhulst

Article by Nick Vlahos: “There is a growing excitement in the democracy field about the potential of citizen’s assemblies (CAs), a practice that brings together groups of residents selected by lottery to deliberate on public policy issues. There is longitudinal evidence to suggest that deliberative mini-publics such as those who meet in CAs can be transformative when it comes to adding more nuance to public opinion on complex and potentially polarizing issues.

But there are two common critiques of CAs. The first is that they are not connected to centers of power (with very few notable exceptions) and don’t have authority to make binding decisions. The second is that they are often disconnected from the broader public, and indeed often claim to be making their own, new “publics” instead of engaging with existing ones.

In this article I propose that proponents of CAs could benefit from the thirty-year history of another democratic innovation—participatory budgeting (PB). There are nearly 12,000 recorded instances of PB to draw learnings from. I see value in both innovations (and have advocated and written about both) and would be interested to see some sort of experimentation that combines PB and CAs, from a decentralized, bottom-up, community-driven approach.

We can and should think about grassroots ways to scale and connect people across geography using combinations of democratic innovations, which along the way builds up (local) civic infrastructure by drawing from existing civic capital (resident-led groups, non-profits, service providers, social movements/mobilization etc.)…(More)”.

Facial Recognition: Current Capabilities, Future Prospects, and Governance

Curated on Posted on by Stefaan Verhulst

A National Academies of Sciences, Engineering, and Medicine study: “Facial recognition technology is increasingly used for identity verification and identification, from aiding law enforcement investigations to identifying potential security threats at large venues. However, advances in this technology have outpaced laws and regulations, raising significant concerns related to equity, privacy, and civil liberties.

This report explores the current capabilities, future possibilities, and necessary governance for facial recognition technology. Facial Recognition Technology discusses legal, societal, and ethical implications of the technology, and recommends ways that federal agencies and others developing and deploying the technology can mitigate potential harms and enact more comprehensive safeguards…(More)”.

Representative Bodies in the Age of AI

Curated on Posted on by Stefaan Verhulst

Report by POPVOX: “The report tracks current developments in the U.S. Congress and internationally, while assessing the prospects for future innovations. The report also serves as a primer for those in Congress on AI technologies and methods in an effort to promote responsible use and adoption. POPVOX endorses a considered, step-wise strategy for AI experimentation, underscoring the importance of capacity building, data stewardship, ethical frameworks, and insights gleaned from global precedents of AI in parliamentary functions. This ensures AI solutions are crafted with human discernment and supervision at their core.

Legislatures worldwide are progressively embracing AI tools such as machine learning, natural language processing, and computer vision to refine the precision, efficiency, and, to a small extent, the participatory aspects of their operations. The advent of generative AI platforms, such as ChatGPT, which excel in interpreting and organizing textual data, marks a transformative shift for the legislative process, inherently a task of converting rules into language.

While nations such as Brazil, India, Italy, and Estonia lead with applications ranging from the transcription and translation of parliamentary proceedings to enhanced bill drafting and sophisticated legislative record searches, the U.S. Congress is prudently venturing into the realm of Generative AI. The House and Senate have initiated AI working groups and secured licenses for platforms like ChatGPT. They have also issued guidance on responsible use…(More)”.

Ground Truths Are Human Constructions

Curated on Posted on by Stefaan Verhulst

Article by Florian Jaton: “Artificial intelligence algorithms are human-made, cultural constructs, something I saw first-hand as a scholar and technician embedded with AI teams for 30 months. Among the many concrete practices and materials these algorithms need in order to come into existence are sets of numerical values that enable machine learning. These referential repositories are often called “ground truths,” and when computer scientists construct or use these datasets to design new algorithms and attest to their efficiency, the process is called “ground-truthing.”

Understanding how ground-truthing works can reveal inherent limitations of algorithms—how they enable the spread of false information, pass biased judgments, or otherwise erode society’s agency—and this could also catalyze more thoughtful regulation. As long as ground-truthing remains clouded and abstract, society will struggle to prevent algorithms from causing harm and to optimize algorithms for the greater good.

Ground-truth datasets define AI algorithms’ fundamental goal of reliably predicting and generating a specific output—say, an image with requested specifications that resembles other input, such as web-crawled images. In other words, ground-truth datasets are deliberately constructed. As such, they, along with their resultant algorithms, are limited and arbitrary and bear the sociocultural fingerprints of the teams that made them…(More)”.

In shaping AI policy, stories about social impacts are just as important as expert information

Curated on Posted on by Stefaan Verhulst

Blog by Daniel S. Schiff and Kaylyn Jackson Schiff: “Will artificial intelligence (AI) save the world or destroy it? Will it lead to the end of manual labor and an era of leisure and luxury, or to more surveillance and job insecurity? Is it the start of a revolution in innovation that will transform the economy for the better? Or does it represent a novel threat to human rights?

Irrespective of what turns out to be the truth, what our key policymakers believe about these questions matters. It will shape how they think about the underlying problems that AI policy is aiming to address, and which solutions are appropriate to do so. …In late 2021, we ran a study to better understand the impact of policy narratives on the behavior of policymakers. We focused on US state legislators,…

In our analysis, we found something surprising. We measured whether legislators were more likely to engage with a message featuring a narrative or featuring expert information, which we assessed by seeing if they clicked on a given fact sheet/story or clicked to register for or attended the webinar.

Despite the importance attached to technical expertise in AI circles, we found that narratives were at least as persuasive as expert information. Receiving a narrative emphasizing, say, growing competition between the US and China, or the faulty arrest of Robert Williams due to facial recognition, led to a 30 percent increase in legislator engagement compared to legislators who only received basic information about the civil society organization. These narratives were just as effective as more neutral, fact-based information about AI with accompanying fact sheets…(More)”

Navigating the Metrics Maze: Lessons from Diverse Domains for Federal Chief Data Officers

Curated on Posted on by Stefaan Verhulst

Paper by the CDO Council: “In the rapidly evolving landscape of government, Federal Chief Data Officers (CDOs) have emerged as crucial leaders tasked with harnessing the power of data to drive organizational success. However, the relative newness of this role brings forth unique challenges, particularly in the realm of measuring and communicating the value of their efforts.

To address this measurement conundrum, this paper delves into lessons from non-data domains such as asset management, inventory management, manufacturing, and customer experience. While these fields share common ground with CDOs in facing critical questions, they stand apart in possessing established performance metrics. Drawing parallels with domains that have successfully navigated similar challenges offers a roadmap for establishing metrics that can transcend organizational boundaries.

By learning from the experiences of other domains and adopting a nuanced approach to metrics, CDOs can pave the way for a clearer understanding of the impact and value of their vital contributions to the data-driven future…(More)”.

How Tracking and Technology in Cars Is Being Weaponized by Abusive Partners

Curated on Posted on by Stefaan Verhulst

Article by Kashmir Hill: “After almost 10 years of marriage, Christine Dowdall wanted out. Her husband was no longer the charming man she had fallen in love with. He had become narcissistic, abusive and unfaithful, she said. After one of their fights turned violent in September 2022, Ms. Dowdall, a real estate agent, fled their home in Covington, La., driving her Mercedes-Benz C300 sedan to her daughter’s house near Shreveport, five hours away. She filed a domestic abuse report with the police two days later.

Her husband, a Drug Enforcement Administration agent, didn’t want to let her go. He called her repeatedly, she said, first pleading with her to return, and then threatening her. She stopped responding to him, she said, even though he texted and called her hundreds of times.

Ms. Dowdall, 59, started occasionally seeing a strange new message on the display in her Mercedes, about a location-based service called “mbrace.” The second time it happened, she took a photograph and searched for the name online.

“I realized, oh my God, that’s him tracking me,” Ms. Dowdall said.

“Mbrace” was part of “Mercedes me” — a suite of connected services for the car, accessible via a smartphone app. Ms. Dowdall had only ever used the Mercedes Me app to make auto loan payments. She hadn’t realized that the service could also be used to track the car’s location. One night, when she visited a male friend’s home, her husband sent the man a message with a thumbs-up emoji. A nearby camera captured his car driving in the area, according to the detective who worked on her case.

Ms. Dowdall called Mercedes customer service repeatedly to try to remove her husband’s digital access to the car, but the loan and title were in his name, a decision the couple had made because he had a better credit score than hers. Even though she was making the payments, had a restraining order against her husband and had been granted sole use of the car during divorce proceedings, Mercedes representatives told her that her husband was the customer so he would be able to keep his access. There was no button she could press to take away the app’s connection to the vehicle.

“This is not the first time that I’ve heard something like this,” one of the representatives told Ms. Dowdall…(More)”.

The 2010 Census Confidentiality Protections Failed, Here’s How and Why

Curated on Posted on by Stefaan Verhulst

Paper by John M. Abowd, et al: “Using only 34 published tables, we reconstruct five variables (census block, sex, age, race, and ethnicity) in the confidential 2010 Census person records. Using the 38-bin age variable tabulated at the census block level, at most 20.1% of reconstructed records can differ from their confidential source on even a single value for these five variables. Using only published data, an attacker can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. The tabular publications in Summary File 1 thus have prohibited disclosure risk similar to the unreleased confidential microdata. Reidentification studies confirm that an attacker can, within blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with nonmodal characteristics) with 95% accuracy, the same precision as the confidential data achieve and far greater than statistical baselines. The flaw in the 2010 Census framework was the assumption that aggregation prevented accurate microdata reconstruction, justifying weaker disclosure limitation methods than were applied to 2010 Census public microdata. The framework used for 2020 Census publications defends against attacks that are based on reconstruction, as we also demonstrate here. Finally, we show that alternatives to the 2020 Census Disclosure Avoidance System with similar accuracy (enhanced swapping) also fail to protect confidentiality, and those that partially defend against reconstruction attacks (incomplete suppression implementations) destroy the primary statutory use case: data for redistricting all legislatures in the country in compliance with the 1965 Voting Rights Act…(More)”.