Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union

Noordt, Colin van; Misuraca, Gianluca

doi:10.1016/j.giq.2022.101714

Cited by 92 publications

(34 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Similar gaps have been documented with regard to gender-based discrimination such as the now-abandoned Amazon AI recruiter that excluded resumes with the word "women" (Dastin, 2018) and the search engines that promote a culture of racism and sexism against Black women (Noble, 2018). Chu et al (2022) introduced a concept known as digital ageism, which is defined as technology-supported prejudice and discrimination against people, especially the elderly, for their age.…”

Section: Discussionmentioning

confidence: 72%

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Nzobonimpa,

Savard

2023

Policy & Internet

View full text Add to dashboard Cite

Many are the promises of artificial intelligence (AI) and algorithms. Governments around the world are increasingly investing in AI and multiple voices have touted this seemingly unmatched revolution. Better performance, cost reduction, efficient management, crime prediction, and prevention are but a few of the pledges of the AI era. While such promises are recognized, research shows that AI benefits could be overstated. Issues of equity, ethics, justice, and fairness have raised concerns and have been seen as potentially threatening democratic principles. As countries get ready to tap into the AI power, researchers are asking whether preparedness is followed by responsibility checks. In this article, we use the Oxford Insights AI Readiness Index to explore why innovation and readiness in artificial intelligence are not always accompanied by accountability, even for some of the most advanced democracies around the world. Using the Fuzzy‐Set Qualitative Comparative Analysis (fsQCA) approach, we show that advancement in AI is not enough: privacy, transparency, inclusion, and accountability principles are key to ensuring governments tackle the AI challenge responsibly.

show abstract

Section: Discussionmentioning

confidence: 72%

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Nzobonimpa,

Savard

2023

Policy & Internet

View full text Add to dashboard Cite

show abstract

“…Greater transparency in the description of these methods could help paint a more accurate picture of the level of adoption of AI in federal agencies. These findings highlight a broader and more important point: while the AI (including deep learning) revolution has rapidly transformed the private sector (Slee, 2020), it appears to have only scratched the surface in public sector applications (Engstrom et al, 2020;van Noordt & Misuraca, 2022).…”

Section: Use Type Examplesmentioning

confidence: 94%

“…Considerations for agency adoption of AI echo private sector considerations-specifically, how can AI be employed as a tool to further process automation, provide insight into data analyses, and improve services (i.e., improve the timeliness and enhance citizen interactions with federal agencies, such as through the use of chatbots) (Congressional Research Service 2021 Artificial Intelligence). Since AI technologies offer unique capabilities, services, and products, as evidenced in smart homes, autonomous vehicles, delivery drones, GPS driving us around, and Amazon's Alexa and other useful virtual assistants in the private sector, we contend AI technologies can promote the productivity and efficiency of the US federal government too as pointed out by some studies (Engstrom et al, 2020;Mehr, 2017), and as has been the case in other countries (van Noordt & Misuraca, 2022;Veale & Brass, 2019). Technology innovation adoption literature is often used to understand how organizations and individuals find out about, decide, and put technology into use (Rogers, 2010;van Oorschot et al, 2018;Wisdom et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

How to Promote AI in the US Federal Government: Insights from Policy Process Frameworks

Khan¹,

Shoaib²,

Arledge³

2023

Preprint

View full text Add to dashboard Cite

When it comes to routine government activities, such as immigration, justice, social welfare provision and climate change, many people believe that the US federal government operates slowly. One potential solution to increase the productivity and efficiency of the federal government is to adopt AI technologies and devices. AI technologies and devices already provide unique capabilities, services, and products, as demonstrated by smart homes, autonomous vehicles, delivery drones, GPS navigation, and virtual assistants such as Amazon's Alexa. However, incorporating massive AI into the US federal government would present several challenges, including ethical and legal concerns, outdated infrastructure, unprepared human capital, institutional obstacles, and a lack of social acceptance. How can US policymakers promote policies that increase AI usage in the face of these challenges? This will require a comprehensive strategy at the intersection of science, policy, and economics that addresses the aforementioned challenges. In this paper, we survey literature on the interrelated policy process to understand the advancement, or lack thereof, of AI in the US federal government, an emerging area of interest. To accomplish this, we examine several policy process frameworks, including the Advocacy Coalition Framework (ACF), Multiple Streams Approach (MSA), Punctuated Equilibrium Theory, Internal Determinants and Diffusion (ID&D), Narrative Policy Framework (NPF), and Institutional Analysis and Development (IAD). We hope that insights from this literature will identify a set of policies to promote AI-operated functionalities in the US federal government.

show abstract

“…The use of AI in business and management tends to have direct implications for firms' profits and consumer welfare (e.g., Cohen et al 2022b;Khernam-nuai et al 2022). Meanwhile, the public sector also utilizes AI in several functions, such as in the legal system (e.g., Cohen et al 2022aCohen et al , 2023 and in policy making (van Noordt and Misuraca 2022). This raises several concerns over the social impact of AI, especially regarding how AI interacts with people (Shin 2023), how people perceive the credibility of AI (Shin 2022), and user awareness of privacy in AI-mediated environments (Shin et al 2022b).…”

Section: Social Impact Of Artificial Intelligencementioning

confidence: 99%

Using AI to detect panic buying and improve products distribution amid pandemic

Adulyasak

Benomar²,

Chaouachi³

et al. 2023

AI & Soc

View full text Add to dashboard Cite

The COVID-19 pandemic has triggered panic-buying behavior around the globe. As a result, many essential supplies were consistently out-of-stock at common point-of-sale locations. Even though most retailers were aware of this problem, they were caught off guard and are still lacking the technical capabilities to address this issue. The primary objective of this paper is to develop a framework that can systematically alleviate this issue by leveraging AI models and techniques. We exploit both internal and external data sources and show that using external data enhances the predictability and interpretability of our model. Our data-driven framework can help retailers detect demand anomalies as they occur, allowing them to react strategically. We collaborate with a large retailer and apply our models to three categories of products using a dataset with more than 15 million observations. We first show that our proposed anomaly detection model can successfully detect anomalies related to panic buying. We then present a prescriptive analytics simulation tool that can help retailers improve essential product distribution in uncertain times. Using data from the March 2020 panic-buying wave, we show that our prescriptive tool can help retailers increase access to essential products by 56.74%.

show abstract

Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union

Cited by 92 publications

References 44 publications

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

Ready but irresponsible? Analysis of the Government Artificial Intelligence Readiness Index

How to Promote AI in the US Federal Government: Insights from Policy Process Frameworks

Using AI to detect panic buying and improve products distribution amid pandemic

Contact Info

Product

Resources

About