Mental health chatbots are AI chatbots that aim to mimic human conversations about how a user feels, help a user work through issues they are facing, suggest wellness exercises to complete, and help track a user’s mood over time. We compare the information disclosure practices and security and privacy concerns of adopters and non-adopters of mental health chatbots. We conducted a survey with 180 participants (30 adopters, 150 non-adopters), collecting data about what information they would hypothetically disclose to mental health chatbots, and concerns they had related to chatbots. We found that compared to non-adopters, adopters were more trusting of chatbots, were willing to reveal more information, perceived security and privacy risks to be less likely, and took fewer precautions.

Decaying representations gradually make social media content less visible to readers over time, which can help users disassociate from past online activities. We explore whether shrinking, one decaying representation, influences managers' assessments and simulated hiring decisions of job candidates, compared to seeing a full profile or an empty profile with no posts. Our 3 x 2 between-subjects crowdsourced survey (N = 360 US managers) shows that shrunk or empty profiles led to more positive decisions than profiles in their original full format. However, shrunk profiles also further contributed to more positive impressions of the candidates. Shrinking did not help the candidate of either gender more than the other and demographics of managers had limited impact on their assessment. Further, our managers regularly search job candidates' social media profiles in real life, suggesting that shrinking could support users' privacy. We finally present implications for individuals' privacy on social media.