An Inconvenient Truth: Algorithmic Transparency &amp; Accountability in Criminal Intelligence Profiling

Zouave, Erik T.; Marquenie, Thomas

doi:10.1109/eisic.2017.12

Cited by 5 publications

(5 citation statements)

References 8 publications

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“…Previous research identifies a lack in the transparency of operations of predictive algorithms used in some smart city infrastructures [2,36]. However, their impact is limited to the cities where these systems operate.…”

Section: Discussionmentioning

confidence: 99%

“…We insist that these standards should be developed by autonomous bodies and not by the entities whose interests lie in the related business. Moreover, as suggested by Zouave and Marquenie [36] and Dilawar et al [77], all stakeholders of the smart city products should be involved while developing these standards.…”

Section: Discussionmentioning

confidence: 99%

“…They found that all these programs failed to provide meaningful transparency to their end-users, that is, the citizens. Zouave and Marquenie [36] assessed to what extent regulatory frameworks addressed the challenges of transparency and accountability in the systems used by law enforcement agencies for the profiling of criminals in smart cities. They discovered that a lack of shared awareness among authorities, developers, and police users introduced gaps that could affect the judgments made by these systems.…”

Section: Transparency and Accountability In Smart Citiesmentioning

confidence: 99%

See 2 more Smart Citations

On Transparency and Accountability of Smart Assistants in Smart Cities

et al. 2019

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Smart Assistants have rapidly emerged in smartphones, vehicles, and many smart home devices. Establishing comfortable personal spaces in smart cities requires that these smart assistants are transparent in design and implementation—a fundamental trait required for their validation and accountability. In this article, we take the case of Google Assistant (GA), a state-of-the-art smart assistant, and perform its diagnostic analysis from the transparency and accountability perspectives. We compare our discoveries from the analysis of GA with those of four leading smart assistants. We use two online user studies (N = 100 and N = 210) conducted with students from four universities in three countries (China, Italy, and Pakistan) to learn whether risk communication in GA is transparent to its potential users and how it affects them. Our research discovered that GA has unusual permission requirements and sensitive Application Programming Interface (API) usage, and its privacy requirements are not transparent to smartphone users. The findings suggest that this lack of transparency makes the risk assessment and accountability of GA difficult posing risks to establishing private and secure personal spaces in a smart city. Following the separation of concerns principle, we suggest that autonomous bodies should develop standards for the design and development of smart city products and services.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Transparency and Accountability In Smart Citiesmentioning

confidence: 99%

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On Transparency and Accountability of Smart Assistants in Smart Cities

et al. 2019

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“…Accountability is important for cases where the use of an ADM system may cause harm to the user, in which case users need to know who is responsible and how to seek redress (Diakopoulos, 2014;Selbst and Powles, 2017). System accountability is highly dependent on transparency since, to achieve accountability, the provider of an ADM system needs to clarify and justify actions, including mitigation and oversight mechanisms for correcting and redressing (Vedder and Naudts, 2017;Zouave and Marquenie, 2017). Thus, following longstanding arguments in the literature on democratic governance (Hood, 2010), we maintain that transparency is a precondition and facilitator of accountability (Diakopoulos and Koliska, 2017) and subsequently impacts perceived accountability (Hood, 2010).…”

Section: Relation Of Transparency To Perceived Fairness Accountabilit...mentioning

confidence: 99%

The public perceptions of algorithmic decision-making systems: Results from a large-scale survey

Aysolmaz

Müller

Meacham

2023

Telematics and Informatics

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“…Some scholars have described the emphasis on risk in criminal justice as entering into an era of actuarial justice [3] in which we focus on analyzing risk in a mathematical way, the rise of 'the logic of risk' [4], or 'the new paradigm of criminal law' [5]. While there are arguments to make in favor of law enforcement agencies making their practices more efficient by using risk profiles [6], this development is not without its issues and raises issues towards those affected by this practice. This leads to the first hypothesis of the paper: risk profiling in the Big Data era creates challenges.…”

Section: Introductionmentioning

confidence: 99%

Risk Profiling by Law Enforcement Agencies in the Big Data Era: Is There a Need for Transparency?

Schendel

2019

Privacy and Identity Management. Fairness, Accountability, and Transparency in the Age of Big Data

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This paper looks at the use of risk profiles by law enforcement in the age of Big Data. First, the paper discusses different use-types of risk profiling. Subsequently, the paper deals with the following three categories of challenges of risk profiling: a) false positives (and to some extent false negatives) as well as incorrect data and erroneous analysis, b) discrimination and stigmatization, c) and maintaining appropriate procedural safeguards. Based on the hypothesis of risk profiling creating challenges, this paper addresses the question whether we need transparency of risk profiling by law enforcement actors, from the perspective of protecting fundamental rights of those affected by the use of risk profiles. The paper explores tackling these challenges from the angle of transparency, introducing Heald's varieties of transparency as a theoretical model.

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An Inconvenient Truth: Algorithmic Transparency & Accountability in Criminal Intelligence Profiling

Cited by 5 publications

References 8 publications

On Transparency and Accountability of Smart Assistants in Smart Cities

On Transparency and Accountability of Smart Assistants in Smart Cities

The public perceptions of algorithmic decision-making systems: Results from a large-scale survey

Risk Profiling by Law Enforcement Agencies in the Big Data Era: Is There a Need for Transparency?

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