Review + personal highlights
Review
Botsman gives a detailed description of the shift of trust: from local to institutional to distributed trust. She gives clear examples of how technology can attribute in the process of determining someone's, or something's, trustworthiness.
Personal highlights
• Financial crisis was not the first and last, but it was a big nail in the coffin of institutional trust. Same for panama papers, Volkswagen scandal, tesco's horsemeat, etc.. p. 3
• Brexit = a symptom of trust shift: from the monolithic to the individualized. But it isn't the age of distrust, it's just a shift. p. 5-6
• Third biggest trust revolution in the history of humankind. From local to institutional to distributed. Other forms willl still persist, just a new dominant form. p. 7
• The explosive growth of the sharing economy is a textbook example of distributed trust at play. It's also why we are feverishly scoring and rating everything. p. 8
• Trust enables us to feel confident enough to take risks and to open ourselves up to being vunerable. p. 16
• Personaized trust: in a person. Generalized trust: trust we attach to an identifiable but anonymous group or thing p. 18
• Definition: Trust is a confident relationship with the unkown. p. 20
• Alibaba, Alipay, TrustPass: examples of how trust was key in the rise of online payments and alibaba. p. 22-23
• Trust leaps are important: they exapnd what is possible, what we can invent and who can be an inventor. Trust leaps extend the reach of our collaboration and creations, opening up new horizons of opportunity. p. 30
• Tuskegee experiment: doctors did terrible experiments on black people to learn about syphilis. This caused a distrust of black people in doctors, making them reluctant to go to the doctor and actually decreasing their life-expectancy of 5 months. p. 33
• Sy trust in so many elite intitutions collapses at the same time: 1) inequality of accountability (certain people are being punished for wrongdoing while others get a leave pass) 2) twilight of elites and authority (the digital age is flattening hierarchies and eroding faith in experts an dthe rich and powerful), 3) segregated echo chambers (living in our cultural ghettoes and being deaf to toher voices). p. 42
• Climbing the trust stack: first you have to trust the idea, then the platform, then the individual. p. 60
• The California Roll principle / Law of Familiarity: In the late '60ties people didn't liked sushi: too strange. Rolling sushi inside out + adding cucumber and familiair ingredients helped. Trust flows easilier if it is something familiar. p. 62
• The What's in it for me principle. The WIIFM factor. p. 68
• Trust influencers, p. 76
• When I get in a car with a stranger, is it the driver I am trusting? Have I placed some faith in Uber, the company, its team? Am I trusting the Uber brand? Perhaps I have cconfidence in the platform itsellf, the app, payments, rating system and its mysterious pricing algorithm? Some of the answers lie in the history of trust between people, companies and brands. p. 88
• With the dawn of social media in the twenty-first centruy, everything canged. Marketers were hit with a seisic shif tin the way trust worked with consumers. It became much harder for brands to exaggerate or make false claims, no matter how flashy their ads. p. 91
• Trust hierarchy of needs, from low to high: identity, security, safety, compatitbility, belonging. p. 93
• Trust is not the same as trustworthiness. Encouring generalized trust simply for the sake of creating a more 'trusting society' is not only meaningless, it's dangerous. For on ething, people are already inclined to want to trust blindly, particularly when greed enters the picturue. We have to look at trustworthiness. p. 112
• Trust signals: status, authority (white lab coat), endorsements of third parties. They change in the age of distributed trust to reviews and ratings for instance p. 115
• UrbanSitter: booking.com for babysitters: the most influential social connection was not the parents rating the sitters, but between the sitters: parents wanted to book the friends of the sitter they really liked. Trust lies within the group with the expertise (the sitters) rather than the group with a similar need (the parents). p. 121
• Trustwortiness is more important (more objective) than trust. Trustworthiness = Is this person competent? Reliable? Honest? p. 123
• Black online market as an example of distributed trust: Turns out, drug dealers care about their online brand and reputation and customer satisfaction as much as Airbnb hosts or ebay sellers. A typical vendor's page will be littered with information, including: how many tansactions they have completed; when the vendor registered; when the vendor last logged in; and their allimportant pseudonym. etc. Vendors put in real effort to demonstrate their trustworthiness. Tehy will even offer free samples p. 140
• Some vendors, eager to build brand, label their drugs as 'fair trade' or 'organic' to appeal to 'ethical' interests. Even 'conflict-free' drugs as brand. p. 141
• 'The real secret of Silk Road is great customer service.'p. 141
• Reputation is trust's closest sibling; the overall opinion of what people think of you. p. 144
• 'Padding feedback'= purchsing your own products on different account and give yourself positive reviews. p. 146
• Social credit score in China: we wil see the birth of reputation black markets selling ways to boost trustworthiness. p .156
• There's a compelling psychological reason people are willing to sign up to systems like this. Seame Credit has tapped into a fundamental aspect of what makes us human: the desire to push oursevles to be better. p. 157
• What will it do to our authenticity when we are tempted 24/7 to act nice to score? Distributed trust could also become networked shame, or turn life in one endless popularity contest. p. 164
• Mark Meadows, founder of Botanic.io: 'all bots should be required to ahve an authenticated identity so we can trust them. Bots need reputation. p. 189
• We are just beginning to udnerstand how anthropomorphism influences trust. It turns out that an autnomous car with a name and voice is perceived as more trustworthy more. p. 193
• Who is to be held responsible for autonomous machines? p. 202
• Blockchain: transfer of assets, supply chain certification, smart contracts. p. 226
• With Blockchain you have to trust the idea of the blockchain and the system. And given that most people lack the technical know-how to understand how the system really works, you have to trust the programmers, miners, entrepeneurs and experts who establish and maintain the cryptographic protocols. p. 230
• More than forty banks have a stake in a consortium called R3CEV to come up with shared standards for blockchains. p. 243
• A challenge: setting up trust systems that can adapt nd keep pace with an unprecendented rate of change. p. 253
• For the moment, at least, we remain in a mindset that wants a benevolent leader, an ultimate decision-maker to take charge and fix the problem. The positive is that all these processes are far more transparent than ever before, as well as under mass observation and open to comment from everyone with at stake in them. p. 254
• Challenge of distributed trust is that many new technologies, from bots to blockchains, either anonymize people or attempt to remove entirely the need to trust another human. Yet it's humans, with all our wonderful kinks and mutations, who make trust possible p. 255
• There is no simple answer to the question 'Who can you trust?' but we do know that ultimately it coes down to a human decidsion. Technology can help us make better and different choices, but in the end it's we who have to decide where to place our trust and who deserves it. p. 256