Editorial: Discrimination in Online Advertising

Cauffman, Caroline

doi:10.1177/1023263x211022526

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…However, it was possible to target based on geography (eg, state or zip code), and in the case of Ovia, the stage of pregnancy and parity. In August 2020, after several lawsuits and scandals surrounding housing discrimination by advertisers, Facebook no longer permitted targeting based on race [ 26 , 27 ]. Given this new policy, researchers in our collaborative were unable to use ads to directly oversample minoritized groups.…”

Section: Key Challenges and Useful Strategiesmentioning

confidence: 99%

Lessons Learned Recruiting and Retaining Pregnant and Postpartum Individuals in Digital Trials: Viewpoint

Parks

Duffecy

McCabe

et al. 2022

JMIR Pediatr Parent

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In an increasingly connected world and in the midst of a global pandemic, digital trials offer numerous advantages over traditional trials that rely on physical study sites. Digital trials have the potential to improve access to research and clinical treatments for the most vulnerable and minoritized, including pregnant and postpartum individuals. However, digital trials are underutilized in maternal and child health research, and there is limited evidence to inform the design and conduct of digital trials. Our research collaborative, consisting of 5 research teams in the U.S. and Australia, aimed to address this gap. We collaborated to share lessons learned from our experiences recruiting and retaining pregnant and postpartum individuals in digital trials of social and behavioral interventions. We first discuss the promise of digital trials in improving participation in research during the perinatal period, as well as the unique challenges they pose. Second, we present lessons learned from 12 completed and ongoing digital trials that have used platforms such as Ovia, Facebook, and Instagram for recruitment. Our trials evaluated interventions for breastfeeding, prenatal and postpartum depression, insomnia, decision making, and chronic pain. We focus on challenges and lessons learned in 3 key areas: (1) rapid recruitment of large samples with a diversity of minoritized identities, (2) retention of study participants in longitudinal studies, and (3) prevention of fraudulent enrollment. We offer concrete strategies that we pilot-tested to address these challenges. Strategies presented in this commentary can be incorporated, as well as formally evaluated, in future studies.

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Section: Key Challenges and Useful Strategiesmentioning

confidence: 99%

Lessons Learned Recruiting and Retaining Pregnant and Postpartum Individuals in Digital Trials: Viewpoint

Parks

Duffecy

McCabe

et al. 2022

JMIR Pediatr Parent

View full text Add to dashboard Cite

show abstract

“…Algorithmic price discrimination [ 16 ], artificial intelligence techniques, and digital system fingerprints [ 15 ] enable the e-commerce company to have the ability of price discrimination. Price discrimination is not only widespread in the field of commodity sales, and there are also discrimination and price difference by using customer information in the field of online car-hailing [ 8 ] and the field of advertising recommendation [ 7 , 17 ]. While consumers benefit from accurate recommendations, sellers may use this information to discriminate on price.…”

Section: Related Literaturementioning

confidence: 99%

“…The Cyberspace Administration of China (CAC) issued the regulations on The Management of Algorithm Recommendation for Internet Information Services to regulate the “big data killing,” stepping into the era of strict supervision of the industry related to algorithm recommendation. The EU also prohibits discrimination on certain grounds and strictly regulates unfair business practices in B2C relationships [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Supervision Strategy Analysis on Price Discrimination of E-Commerce Company in the Context of Big Data Based on Four-Party Evolutionary Game

Xiao

2022

Computational Intelligence and Neuroscience

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This paper focuses on the phenomenon of “big data killing” implied in e-commerce and discusses how to take the government as the lead to coordinately supervise the price discrimination behavior of e-commerce companies towards loyal customers. First, the four-party evolutionary game model of the government regulatory department, e-commerce platform, e-commerce company, and consumer is built. Second, the stability of the strategy choice of each game subject is analyzed. On this basis, the evolutionary stable strategy in the system based on First Law of Lyapunov is explored. Finally, the influences of key elements on system evolution are simulated and analyzed by MATLAB2021. Results demonstrate that (1) the government supervision mechanism can effectively supervise the price discrimination of e-commerce company based on big data to loyal customers; (2) when the government chooses the strict supervision strategy, reducing the information supervision cost of the e-commerce platform and the strict supervision cost of the government enable the government and the e-commerce platform to coordinate supervision and make the e-commerce company incline to choose the nondifferential pricing strategy; (3) when the government chooses the loose supervision strategy, reducing the information supervision cost of the e-commerce platform and increasing the probability of consumer discovering differential pricing and the penalties for differential pricing of e-commerce company enable the e-commerce platform and consumer to coordinate supervision, and make the e-commerce company incline to choose the nondifferential pricing strategy. The results of this study can provide theoretical guidance for the government and companies to make beneficial strategic decisions in the development of e-commerce.

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When Serving the Public Interest Generates Private Gains: Private Actor Governance and Two-Sided Digital Markets

Beaumier,

Newman

2024

Perspect. polit.

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From speech to privacy, broad public interests are increasingly governed online by policy decisions taken by private companies. We examine when and how firms make such decisions. In contrast to the shadow of hierarchy and functionalist explanations of private authority, we build an analytical framework based on business power and the economics literature concerned with two-sided markets. We argue that companies operating as digital platforms may use private actor governance to consolidate their influence. More precisely, public-interest regulation on one side of the market (e.g., protecting the privacy of end-users) may increase the dependence of firms on the other side of the market (e.g., increasing the price paid for information by advertisers). We probe our argument by looking at the privacy policy implemented by Apple in 2021. Our findings demonstrate the growing role played by digital companies in global regulatory debates and call attention to how market structures can simultaneously incentivize public-interest regulation and become a source of business power.

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Editorial: Discrimination in Online Advertising

Cited by 5 publications

References 2 publications

Lessons Learned Recruiting and Retaining Pregnant and Postpartum Individuals in Digital Trials: Viewpoint

Lessons Learned Recruiting and Retaining Pregnant and Postpartum Individuals in Digital Trials: Viewpoint

Supervision Strategy Analysis on Price Discrimination of E-Commerce Company in the Context of Big Data Based on Four-Party Evolutionary Game

When Serving the Public Interest Generates Private Gains: Private Actor Governance and Two-Sided Digital Markets

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