Algorithmic systems: the consent is in the detail?

Γιαννοπούλου, Αλεξάνδρα

doi:10.14763/2020.1.1452

Cited by 13 publications

(10 citation statements)

References 21 publications

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“…The privacy-related issues of AI-PID data requirements raise informed consent concerns (Kim & Bodie, 2021). Informed consent is the principle that data owners should be notified about what data will be collected and how it will be used before collection (Giannopoulou, 2020). One challenge of today’s data ecosystem is that the assumption is once consent is given it is always given (Froomkin, 2019; Leetaru, 2019).…”

Section: Artificial Intelligence and Pay Information Disclosure Chall...mentioning

confidence: 99%

Artificial Intelligence and Pay Information Disclosure: Changing How Pay is Communicated

Nyberg

Cragun

Conroy

2023

Compensation & Benefits Review

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Pay information disclosure (PID), or communicating pay information between and among actors, affects employees, organizations, and societies. Disruptions resulting from artificial intelligence (AI) will also change how pay is communicated. Based on AI, AI and human resources (HR), and PID, as well as anecdotal data involving organizations that are integrating AI in their pay practices, we introduce areas of AI relevant to PID and describe opportunities and challenges. HR should play a critical role in developing employee trust in AI systems by protecting employee privacy, training AI on high-quality data, and ensuring AI algorithms are ethical. AI can transform PID by supporting advanced pay methodologies, reducing barriers to sharing information, and educating employees. However, research needs to be conducted on all of these areas and practitioners should strive to keep an open, but cautious mind about both the benefits and challenges of integrating AI into HR practices.

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Section: Artificial Intelligence and Pay Information Disclosure Chall...mentioning

confidence: 99%

Artificial Intelligence and Pay Information Disclosure: Changing How Pay is Communicated

Nyberg

Cragun

Conroy

2023

Compensation & Benefits Review

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“…Model cards and similar standardized artifacts can play a role in processes for governance and accountability of AI/ML systems. As many have studies have reinforced, mechanisms for governance and accountability of technical systems are prerequisites for informed consent [12,22,69] and equity [18,37,38]. Algorithmic audits are a key strategic approach toward governance and accountability.…”

Section: Background and Related Workmentioning

confidence: 99%

Interactive Model Cards: A Human-Centered Approach to Model Documentation

Crisan,

Drouhard,

Vig

et al. 2022

Preprint

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Deep learning models for natural language processing (NLP) are increasingly adopted and deployed by analysts without formal training in NLP or machine learning (ML). However, the documentation intended to convey the model's details and appropriate use is tailored primarily to individuals with ML or NLP expertise. To address this gap, we conduct a design inquiry into interactive model cards, which augment traditionally static model cards with affordances for exploring model documentation and interacting with the models themselves. Our investigation consists of an initial conceptual study with experts in ML, NLP, and AI Ethics, followed by a separate evaluative study with non-expert analysts who use ML models in their work. Using a semi-structured interview format coupled with a think-aloud protocol, we collected feedback from a total of 30 participants who engaged with different versions of standard and interactive model cards. Through a thematic analysis of the collected data, we identified several conceptual dimensions that summarize the strengths and limitations of standard and interactive model cards, including: stakeholders; design; guidance; understandability & interpretability; sensemaking & skepticism; and trust & safety. Our findings demonstrate the importance of carefully considered design and interactivity for orienting and supporting non-expert analysts using deep learning models, along with a need for consideration of broader sociotechnical contexts and organizational dynamics. We have also identified design elements, such as language, visual cues, and warnings, among others, that support interactivity and make non-interactive content accessible. We summarize our findings as design guidelines and discuss their implications for a human-centered approach towards AI/ML documentation.CCS Concepts: • Computing methodologies → Natural language processing; • Human-centered computing → Visualization;Human computer interaction (HCI); Interaction design process and methods.

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“…Furthermore, the GDPR does not contain direct obligations for software developers (Bygrave, 2017), and the allocation of responsibility for data processing remains a topic of contentious debate. This is why Giannopoulou (2020) argued that 'more focus should be placed on the level at which privacy design decisions are truly taken and that is at an infrastructural level currently not taken into consideration within the accountability structure of the GDPR' . Especially in the tracking ecosystem, a small number of tracker companies develop the dominant tracking technologies, and ship these to app developers in the form of pre-made tracking libraries.…”

Section: Challenges To the Effectiveness Of Gdprmentioning

confidence: 99%

Before and after GDPR: tracking in mobile apps

Kollnig¹,

Binns²,

Kleek³

et al. 2021

Internet Policy Review

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Third-party tracking, the collection and sharing of behavioural data about individuals, is a significant and ubiquitous privacy threat in mobile apps. The EU General Data Protection Regulation (GDPR) was introduced in 2018 to protect personal data better, but there exists, thus far, limited empirical evidence about its efficacy. This paper studies tracking in nearly two million Android apps from before and after the introduction of the GDPR. Our analysis suggests that there has been limited change in the presence of third-party tracking in apps, and that the concentration of tracking capabilities among a few large gatekeeper companies persists. However, change might be imminent.

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Algorithmic systems: the consent is in the detail?

Cited by 13 publications

References 21 publications

Artificial Intelligence and Pay Information Disclosure: Changing How Pay is Communicated

Artificial Intelligence and Pay Information Disclosure: Changing How Pay is Communicated

Interactive Model Cards: A Human-Centered Approach to Model Documentation

Before and after GDPR: tracking in mobile apps

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