Familiarity transposes existing stances

If a new person/object demonstrates traits of something/somebody we are used to trusting, we are more likely to shift our existing trust to this new entity. Similarly, distrust and other sentiments may also work in the same way.

• ‘Mere-exposure effect’ or ‘Law of Familiarity’ (by Professor Robert B. Zajonc) explains that humans have a tendency to be more comfortable around people or like things more when they are familiar to us. This helps to ease establishing trust at the first step (Botsman; ch. 3).
• When we are in a situation which makes us cognitively at ease, we feel it familiar, true, good(-natured; hence liking, cf. exposure effect), and effortless. Our thinking tends to be more casual and superficial. When we are cognitively strained, we are more likely to be vigilant (cf. evolution), suspicious (cf. social system), invest more effort in the doing, feel less comfortable, make fewer errors but become less intuitive and less creative (Kahneman; ch. 5).

The same applies to our relation with (humanoid) robots.

• Anthropomorphism (displaying human characters in robots) can help establish human trust, until the point when it is almost perfect but not yet (mixed feeling of creepiness and fascination). Masahiro Mori (robotics professor at Tokyo Institute of Technology) believes once that point is passed, perceived image will become again positive (Botsman; ch. 8).
• People are more forgiving and recognising towards machines which show human faculties (e.g. emotions, faults and sympathy) than perfect, cold machines (cf. Bert C, the sous-chef bot). ‘If you think machines are perfect and then they make a mistake, you don’t trust them again,’ says Frank Krueger, cognitive psychologist and neuroscientist at George Mason University, expert on human-to-machine trust. (Botsman 181–183)

This familiarity, however, can be manipulated for deceiving people.

• Illusion of information can be more dangerous than ignorance (cf. story of the deceitful nanny Doris from The Lady magazine and how she tricked Botsman’s family into believing her identity) (Botsman; ch. 5).
• Familiarity boosts trustworthiness of something we would access. For example, if people have seen a similar headline often, they would increasingly be prone to believing it (Singer and Emerson; ch. 5).
• Note that anthropomorphism for the sake of building human trust can be done in parallel and independently of performing machine’s principal task (cf. People blame less self-driving program with a human voice – not even a body – when a programmed crash happens in a simulation test experience). (Botsman 198–202)

This also explains why intuition based on past experiences and/or expertise may not be reliable, as we may conflate an apparently familiar object/event too soon with what we know whilst they can be actually dissimilar (Kahneman; ch. 21 & 22).
==> [Intuition is feeble and unreliable]

We are used to scanning for familiar traits when we encounter unfamiliar matters or situations, especially when we need to deal with the unfamiliar matters/situations.

• When we predict outcome in the future or make a decision on it, we often regress to similar, instantaneous, representative events which are temporally more available to us (e.g. grading a particular student project will make reference for grading their GPA at graduation when we are asked to project it).
• We generalise the obvious, known instance to place our judgement for the unknown. However, from the point of the obvious, known instance to the point where the final event happens, there are still various factors which can affect to eventual outcome.
• To moderate bias, We can relativise our judgement by taking the known instance as just a base rate, then consider other possible factors, then the available data about all these factors, before finally making a decision. Often we will, hence, obtain a relative regression towards the mean (Kahneman; ch. 18).

Last update: 2021-01-24

References

Botsman, Rachel. Who Can You Trust? How Technology Brought Us Together and Why It Might Drive Us Apart. Perseus Books, 2017.

Kahneman, Daniel. Thinking, Fast and Slow. 1st ed., Farrar, Straus and Giroux, 2011.

Singer, P. W. and Emerson T. Brooking. LikeWar: The Weaponization of Social Media. Houghton Mifflin Harcourt, 2018.