Getty Images executive photographs (licensed)

Licensed: not exercised here

Getty Images is a paid licensed product, so it carries no provenance badge: the access path below was not run in this session. Treat it as unverified until someone exercises it through a Getty Images licence. This is the honest grade under the institute’s Verified discipline.

Getty Images is a stock and editorial photo agency whose dated editorial photographs of public figures let researchers assemble time-stamped image sets for named executives. Paired with a facial-analysis model, the photos yield apparent-age and other face-based measures over time. A paper we distill uses it: Borgschulte, Guenzel, Liu & Malmendier build a CEO Apparent Aging Data Set of 3,002 dated photographs of 453 Fortune 1000 CEOs (the 2006 cohort), spanning 2000 to 2016, sourced from Getty Images (supplemented with Google Images), and run a deep convolutional apparent-age model to show that industry distress visibly ages CEOs.

• Cost: licensed, per-image or subscription editorial licence.
• Vendor: Getty Images.
• Coverage: editorial / press photographs of public figures with capture dates and captions; depth depends on how often a person was photographed, so prominent executives are well covered and others sparsely.

Access (when licensed)

• Through a Getty Images licence. Images are searched and licensed on the Getty platform (editorial collection); the date and caption metadata, needed to place each photo in time, come with the image.
• Build a per-person, per-date image set. A usable dataset is the set of dated photos for each named individual; the research asset is the derived measure (apparent age), not the images themselves.
• Respect the editorial licence. Getty terms restrict redistribution and some automated use; store derived features and licence the images properly. Keep any credentials in .env, never hard-coded.

Gotchas (the ones that bite pipelines)

These are the failure modes to expect; they are documented, not verified here.

• Capture date versus publication date. The research date must be when the photo was taken, not when it was uploaded or republished; a wrong date corrupts any aging trajectory. Verify the capture date, not just the metadata timestamp.
• Photo selection is endogenous. Which photos exist and get licensed depends on events (a CEO is photographed more during a crisis), and editorial photos are retouched, lit, and posed differently; both confound a face-based measure. The citing paper uses a difference-in-differences design over many images per person to net out fixed appearance. Account for selection.
• Model bias and validation. Apparent-age and facial models carry systematic error by lighting, pose, expression, gender, and race; the measure is only as good as the model’s validation on this population. State the model and its validation.
• Coverage is uneven across people and time. Some CEOs have many dated photos, others very few; sparse coverage makes per-person trajectories noisy and biases toward the most-photographed. Report images per person.
• Mixing sources changes the distribution. Supplementing Getty with Google Images (as the citing paper does) mixes editorial and web images with different quality and date reliability; treat source as a covariate, not as interchangeable.

Citation

Cite the source and that a measure was derived, e.g.: Editorial photographs licensed from Getty Images, accessed YYYY-MM-DD. State the population, the number of images and dates, any supplementary image source, and the facial model used to derive the measure.