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SUMMARY:AI in disguise: AI-generated ads outperform human-made ads if they
  don't look like AI - Prof Jochen Hartmann (Technical University of Munich
 )
DTSTART;VALUE=DATE-TIME:20240228T170000Z
DTEND;VALUE=DATE-TIME:20240228T180000Z
UID:https://talks.ox.ac.uk/talks/id/eddeb941-e14c-4cd1-b061-6155411e094d/
DESCRIPTION:2023 was the year of generative AI. Its advance sparked the im
 agination about the role of generative AI in creative industries in genera
 l and advertising in particular\, and raised the question whether it can a
 ctually disrupt the advertising industry. Answering this question is nearl
 y impossible using individual A/B tests as these only provide a snapshot i
 nto specific application contexts\, which are subject to the researchers
 ’ discretion. To address this question\, we partner with a leading onlin
 e ad platform\, which released a generative AI-powered ad maker in 2023\, 
 to obtain a dataset covering more than 2 million daily ad-level observatio
 ns across various industries. This dataset includes both human-made and AI
 -generated ads in a quasi-experimental setting.\n\nIn our quasi-experiment
 al setting of ads that were created by the same advertiser at the same tim
 e\, and as part of the same campaign but vary in terms of the usage of AI\
 , we find that the click-through rates (CTRs) are higher if advertisers em
 ploy AI to generate advertising images\, but not necessarily for the ad ca
 ption. Interestingly\, this superiority of AI images holds only if the AI-
 generated images do not look like AI. We find that AI images are more like
 ly to include a human face\, but the presence of a human face tends to dis
 guise the ad as being generated by AI. Our findings provide evidence that 
 advertisers can benefit from leveraging mass-market generative AI tools to
  boost their online ad performance.\n\nJochen Hartmann’s research is sit
 uated at the intersection of digital marketing and machine learning\, with
  a focus on the analysis of unstructured data (computer vision\, natural l
 anguage processing) and generative artificial intelligence (AI). His subst
 antive research interests encompass social media\, multimodal digital adve
 rtising\, algorithmic fairness\, diversity in advertising\, and human-mach
 ine interactions. His work has been published in journals such as Proceedi
 ngs of the National Academy of Sciences (PNAS)\, Journal of Marketing Rese
 arch\, Journal of Consumer Psychology\, and International Journal of Resea
 rch in Marketing (among others). His work on text and image mining is amon
 g the most read and most cited articles in high-ranking marketing journals
 . He is also a co-author of book chapters on machine learning and natural 
 language processing.\nIn January 2023\, Jochen Hartmann was appointed to t
 he Professorship of Digital Marketing at TUM School of Management in Munic
 h. Prior to that\, he was an assistant professor at the Faculty of Economi
 cs at the University of Groningen. He earned his doctoral degree from the 
 University of Hamburg. Before his doctorate\, he worked as a management co
 nsultant at McKinsey & Company. Jochen Hartmann is a regular visiting scho
 lar at Columbia Business School and a lecturer in machine learning at Mann
 heim Business School and Vienna University of Economics and Business. Joch
 en Hartmann is a member of the DFG-funded scientific network “AI algorit
 hms for decision-making in businesses and organizations”.\nSpeakers:\nPr
 of Jochen Hartmann (Technical University of Munich)
LOCATION:1 St Giles' (Seminar Room or on Zoom)\, 1 St Giles' OX1 3JS
TZID:Europe/London
URL:https://talks.ox.ac.uk/talks/id/eddeb941-e14c-4cd1-b061-6155411e094d/
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DESCRIPTION:Talk:AI in disguise: AI-generated ads outperform human-made ad
 s if they don't look like AI - Prof Jochen Hartmann (Technical University 
 of Munich)
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