Several Topics on: Decision Making with Algorithms



Lehr- und Forschungsgebiet Dienstleistungs- und Technologiemarketing


Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes (Dietvorst et al. 2015)

Implementing algorithms in our everyday lives (e.g. facial recognition technology, autonomous vehicles, decision assistance, medical decisions) will be the future and research is developing rapidly in this field. Thus, understanding the dynamics of decisions and behaviors when confronted with a decision on an implementation algorithms for many scenarios are valuable.

Exemplary Topics:
• Evaluation of implementing Facial Recognition Algorithms in a retail setting (e.g. cost savings through theft prevention vs. surveillance)
• Decision assisted by algorithms (e.g. judges assessing reoffender probabilities of convicts) may lead to discrimination based on historical data. Evaluation of discrimination by algorithms in multiple settings (Hiring decisions, gender, autonomous robot decisions etc.)
• Evaluation of responsiblity for algorithmic decisions (e.g. car crash: software decides to crash self instead of driving into people) Who is attributed responsibility? (Programmer, company, softwarecompany etc.)

Note: You do not need any programming skills for algorithms, as these topics deal with the attitide or perception of algorithms - not the development of new algorithms

Your tasks
• Summary and evaluation of existing literature and applications
• Further literature research
• Analysis of algorithmic decision outcome
• Assessment of managerial implications for companies