Black–White Wage Differentials in a Multiple Sample Selection Bias Model

Baffoe-Bonnie, John

doi:10.1007/s11293-008-9150-x

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…Existing works examine feedback loops in the single-agent setting [64], with particular branches proposing metrics to recover counterfactuals of consumer preferences fixing consumer strategy [65,66]. The effects of competition in ML holds significant implications to sociology [67,68], economics [69,70,71], electoral systems [72,73], and recommendation systems [74,75,76,77]. [78] studies an interesting but substantially different model of bandits in matching markets.…”

Section: A2 Feedback Loops In ML Systemsmentioning

confidence: 99%

Competing AI: How does competition feedback affect machine learning?

Ginart,

Zhang,

Kwon

et al. 2020

Preprint

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This paper studies how competition affects machine learning (ML) predictors. As ML becomes more ubiquitous, it is often deployed by companies to compete over customers. For example, digital platforms like Yelp use ML to predict user preferences and make recommendations. A service that is more often queried by users, perhaps because it more accurately anticipates user preferences, is also more likely to obtain additional user data (e.g. in the form of a Yelp review). Thus, competing predictors cause feedback loops whereby a predictor's performance impacts what training data it receives and biases its predictions over time. We introduce a flexible model of competing ML predictors that enables both rapid experimentation and theoretical tractability. We show with empirical and mathematical analysis that competition causes predictors to specialize for specific sub-populations at the cost of worse performance over the general population. We further analyze the impact of predictor specialization on the overall prediction quality experienced by users. We show that having too few or too many competing predictors in a market can hurt the overall prediction quality. Our theory is complemented by experiments on several real datasets using popular learning algorithms, such as neural networks and nearest neighbor methods.

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Section: A2 Feedback Loops In ML Systemsmentioning

confidence: 99%

Competing AI: How does competition feedback affect machine learning?

Ginart,

Zhang,

Kwon

et al. 2020

Preprint

View full text Add to dashboard Cite

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Cash and Distressed House Sales Price Discounts: Dual Sample Selection Spatial Interdependence Approaches

Tidwell

Jauregui

Sah

et al. 2016

J Real Estate Finan Econ

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The costs of racism on workforce entry and work adjustment.

Perry

Pickett

2016

The Cost of Racism for People of Color: Contextualizing Experiences of Discrimination.

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From a historical standpoint, the role of racism in the field of career development and career counseling, also referred to as vocational psychology, has not garnered much scholarly interest or empirical attention. The relative absence of this topic in contemporary research and theory, unfortunately, continues to relegate racism in all of its forms to a fringe interest. Although nearly all of the major theories in the field have been examined within the context of race, such as testing propositions among people of color or comparing measures between different groups, very few studies have actually investigated racism in direct relation to their principles and constructs. Overall, the knowledge base of the costs of racism is piecemeal and isolated.According to Fouad and Kantamneni's (2013) review of career choice and development, empirical efforts to generally understand the role of race, ethnicity, culture, and discrimination are preliminary, requiring far more research.

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Black–White Wage Differentials in a Multiple Sample Selection Bias Model

Abstract: Black and white wage differential, Multiple sample selection bias, Sequential decisions, J31,

Cited by 5 publications

References 14 publications

Competing AI: How does competition feedback affect machine learning?

Competing AI: How does competition feedback affect machine learning?

Cash and Distressed House Sales Price Discounts: Dual Sample Selection Spatial Interdependence Approaches

The costs of racism on workforce entry and work adjustment.

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