Trust

Business Psychology
In this post, I summarise some of my notes on the work of Rachel Botsman on Trust. Botsman is the co-author of ‘What’s Mine Is Yours’, which was part of the inspiration behind one of my previous posts (The Sharing Economy – link).
She has equally interesting TED talks in sharing economy and specifically on the concept of trust as a currency and glue for those marketplaces, all of those are highly recommended and can be found here.
Below are my notes on some of those TED talks and articles:

Case Study: Bla Bla Car
  • In this famous sharing marketplace, the average ride length is 320km. It is not surprising that one of the metric to choose the user to share the trip with is how ‘talkative’ he/she is. (Bla, Bla Bla, Bla Bla Bla).
  • This is one of the information provided by this service, which in aggregate allow people to make a decision which is against what they were taught in their youth, that is, “Never get in a car with a stranger”. In fact, Bla Bla Car today is moving 4 million people per month, versus 870k monthly commuters in the Eurostar.
This is a good example of how technology allows millions of people to take a Trust Leap:
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A Trust Leap is when we take the risk to do something new or different from the way we have always done it:
  • To jump from the known to the unknown you need a force to pull you over the gap, that force is trust.
  • Trust is often defined as a risk assessment on whether things will go right, but that makes trust sound rational and predictable, it is more accurately defined by a confident relationship with the unknown.
This confident relationship with the unknown is built with layers of trust, i.e. the Trust Stack:
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  1. You first have to trust the idea. You fundamentally trust the concept of a marketplace of people sharing long rides.
  2. Then you have to trust the platform. Essentially trusting the implementation of the idea –  would Bla Bla car help you if you needed it? How would you get comfortable that the reviews in there are reliable, etc.
  3. Finally, you have to trust the other user. Once the above is granted, you still need to pick the user that you consider most trustworthy in the platform according to your own perception and to the key metrics given.
 
Evolution of Trust:
We have seen only three types of trust so far. The shifts among these three phases were driven by technology and the willingness to scale. However, the underpinning need for “trust” in a business transaction has never changed.
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  1. Local Trust – based on the primitive concept of “village accountability”. Trust and reputation were a pillar of the success of an individual within his social context, betraying the trust of someone had a direct impact on the future ability of that individual to transact with others.
  2. Institutional Trust – as technology (e.g. transportation) increased the boundaries of the “village” in a business sense, people started to place trust in black box systems of authority such as legal contracts, institutions, governments etc. Trust becomes institutionalised and permission based.
    • In this model, trust between peers becomes Opaque, Closed, Centralised, Licensed, Top-down.
    • Institutional trust, however, seems to be under continuous challenges in the digital age, an alternative model is emerging.
  3. Distributed Trust – DNA of peer trust is built on Transparent, Inclusive, Decentralised, Accountable, Bottom up.
    • Trust has been unbundled from central authorities and inverted to become bottom up.
    • An example could be the change of behaviour that reputation systems with mutual (seller and buyer) ratings are having.
    • Botsman has a great example in an HBR article (link)
      I used too many towels and carelessly left them on the floor. It’s not something I’ve thought much about before: I leave the hotel and who’s to know? But something struck me as I walked out the door. I would never do this as a guest staying in a place on Airbnb. I behave differently because of the reputation system in place that means not only do I rate hosts, but they rate me. Trust lies intimately between the perceptions of the two users.
    • This model re-introduces the accountability that made local trust networks so valid, but in ways and on a scale never seen before.

Technology such as Blockchain, which in its simplest definition is a ledger of assets, which are followed and recorded in their movement through the network, is indeed working on these same assumptions. By making the trust leap reliable only on the first two elements of the stack, idea and platform, it allows transactions between anonymous actors to be something which is actually feasible, and scalable.

Conclusion:

Once a trust shift has happened around an idea or a behaviour you cannot reverse the story, and without a doubt some of these shifts will be messy (e.g. uber).
The focus will eventually move away from the technology underneath this paradigm shift, and we will probably realise that we are simply converging to the digital version of the trust model we followed for so long before we had to compromise it for scalability when tools such as distributed networks were not available.

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