Good news is better than bad news, but bad news is not worse than no news

Did you hear that students' knowledge of multiplication basic facts improved decidedly between the second national mathematics assessment in 1978 and the third assessment in 1982 (NAEP 1983)? Average scores of nine-year-olds rose from 60 percent to 66 percent, ranging from 70–85 percent on easier facts to 50–60 percent on harder facts. Fourth graders performed about forty percentage points better than third graders. By age thirteen. scores were 90 percent or above on both assessments. That's the good news. The bad news is that results were not as good for conceptual, computational. or problem-solving items.

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Concern for Others Leads to Vicarious Optimism

Psychological Science ◽

10.1177/0956797617737129 ◽

2018 ◽

Vol 29 (3) ◽

pp. 379-389 ◽

Cited By ~ 6

Author(s):

Andreas Kappes ◽

Nadira S. Faber ◽

Guy Kahane ◽

Julian Savulescu ◽

Molly J. Crockett

Keyword(s):

Bad News ◽

Good News ◽

Concern For Others ◽

Future Events ◽

Better Than

An optimistic learning bias leads people to update their beliefs in response to better-than-expected good news but neglect worse-than-expected bad news. Because evidence suggests that this bias arises from self-concern, we hypothesized that a similar bias may affect beliefs about other people’s futures, to the extent that people care about others. Here, we demonstrated the phenomenon of vicarious optimism and showed that it arises from concern for others. Participants predicted the likelihood of unpleasant future events that could happen to either themselves or others. In addition to showing an optimistic learning bias for events affecting themselves, people showed vicarious optimism when learning about events affecting friends and strangers. Vicarious optimism for strangers correlated with generosity toward strangers, and experimentally increasing concern for strangers amplified vicarious optimism for them. These findings suggest that concern for others can bias beliefs about their future welfare and that optimism in learning is not restricted to oneself.

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EXPRESS: Bad News? Send an AI. Good News? Send a Human

Journal of Marketing ◽

10.1177/00222429211066972 ◽

2021 ◽

pp. 002224292110669

Author(s):

Aaron M. Garvey ◽

TaeWoo Kim ◽

Adam Duhachek

Keyword(s):

Artificial Intelligence ◽

Bad News ◽

Good News ◽

Consumer Responses ◽

Consumer Resistance ◽

Ethical Concerns ◽

Human Agent ◽

Purchase Likelihood ◽

To Receive ◽

Better Than

The present research demonstrates how consumer responses to negative and positive offers are influenced by whether the administering marketing agent is an Artificial Intelligence (AI) or a human. In the case of a product or service offer that is worse than expected, consumers respond better when dealing with an AI agent in the form of increased purchase likelihood and satisfaction. In contrast, for a better than expected offer, consumers respond more positively to a human agent. We demonstrate that AI agents, in comparison to human agents, are perceived to have weaker intentions when administering offers, which accounts for this effect. That is, consumers infer that AI agents lack selfish intentions in the case of an offer that favors the agent and lack benevolent intentions in the case of an offer that favors the customer, thereby dampening the extremity of consumer responses. Moreover, we demonstrate a moderating effect such that marketers may anthropomorphize AI agents to strengthen perceived intentions, providing an avenue to receive due credit from consumers when providing a better offer and mitigate blame when providing a worse offer. Potential ethical concerns with the use of AI to bypass consumer resistance to negative offers are discussed.

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Concern for Others Leads to Vicarious Optimism

10.31234/osf.io/na9db ◽

2018 ◽

Cited By ~ 1

Author(s):

Andreas Kappes ◽

Molly Crockett ◽

Nadira Sophie Faber ◽

Julian Savulescu ◽

Guy Kahane

Keyword(s):

Bad News ◽

Good News ◽

Concern For Others ◽

Future Events ◽

Better Than

An optimistic learning bias leads people to update their beliefs in response to better-than-expected “good news”, but neglect worse-than-expected “bad news”. Because evidence suggests this bias arises from self-concern, we hypothesized that a similar bias may affect beliefs about others’ future, to the extent that people care about others. Here, we demonstrate the phenomenon of vicarious optimism and show that it arises from concern for others. Participants predicted the likelihood of unpleasant future events that could happen to either themselves or others. In addition to showing an optimistic learning bias for events affecting themselves, people showed vicarious optimism when learning about events affecting friends and strangers. Vicarious optimism for strangers correlated with generosity toward strangers, and experimentally increasing concern for strangers amplified vicarious optimism for them. These findings suggest that concern for others can bias beliefs about their future welfare and that optimism in learning is not restricted to oneself.

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Optimistic reinforcement learning: computational and neural bases

10.1101/038778 ◽

2016 ◽

Cited By ~ 3

Author(s):

Germain Lefebvre ◽

Mael Lebreton ◽

Florent Meyniel ◽

Sacha Bourgeois-Gironde ◽

Stefano Palminteri

Keyword(s):

Reinforcement Learning ◽

Instrumental Learning ◽

Learning Task ◽

Bad News ◽

Good News ◽

Life Outcomes ◽

Optimism Bias ◽

Reward Circuitry ◽

High Level ◽

Better Than

While forming and updating beliefs about future life outcomes, people tend to consider good news and to disregard bad news. This tendency is supposed to support the optimism bias. Whether this learning bias is specific to high-level abstract belief update or a particular expression of a more general low-level reinforcement learning process is unknown. Here we report evidence in favor of the second hypothesis. In a simple instrumental learning task, participants incorporated better-than-expected outcomes at a higher rate compared to worse-than-expected ones. In addition, functional imaging indicated that inter-individual difference in the expression of optimistic update corresponds to enhanced prediction error signaling in the reward circuitry. Our results constitute a new step in the understanding of the genesis of optimism bias at the neurocomputational level.

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