  In credence goods markets such as health care or repair services, consumers
rely on experts with superior information to adequately diagnose and treat
them. Experts, however, are constrained in their diagnostic abilities, which
hurts market efficiency and consumer welfare. Technological breakthroughs that
substitute or complement expert judgments have the potential to alleviate
consumer mistreatment. This article studies how competitive experts adopt novel
diagnostic technologies when skills are heterogeneously distributed and
obfuscated to consumers. We differentiate between novel technologies that
increase expert abilities, and algorithmic decision aids that complement expert
judgments, but do not affect an expert's personal diagnostic precision. We show
that high-ability experts may be incentivized to forego the decision aid in
order to escape a pooling equilibrium by differentiating themselves from
low-ability experts. Results from an online experiment support our hypothesis,
showing that high-ability experts are significantly less likely than
low-ability experts to invest into an algorithmic decision aid. Furthermore, we
document pervasive under-investments, and no effect on expert honesty.
