The Dot Collector as a Oneslate foil: tools for idea meritocracy

Why consider Dot Collector and idea meritocracy?

The Dot Collector software at Bridgewater Associates was described as a tool for enabling “idea meritocracy” by the investment management firm’s founder, Ray Dalio, in his 2017 TED talk, “How to build a company where the best ideas win” [0]. The path to idea meritocracy enabled by Dot Collector, as described in the talk, includes

  • radical truthfulness and
  • radical transparency.

Ray’s story about coming to value such concepts, and his insights about how the Dot Collector’s use, paint a picture of how data from systems collecting candid beliefs and attribute evaluations not only can, but do, really strategically aid in making collective decision valuable. Beyond collecting opinions and evaluations, he describes the critical steps of

  • implementing found principles into algorithms and
  • interpreting the data along with human thought

to help inform and advise decision making within the organization.

The intention Ray reveals is not just to float to some lofty, ideal mode of operation.  One purpose for acting on the best available information in his case has been to “bet against the consensus and be right because the consensus is built into the price”–that is, to make money through market transactions.  Idea meritocracy usefully applies to multiple aspects of his firm, he elaborates, including more accurately evaluating internal survey data (possibly flipping the results), suggesting project work, informing team composition, etc.

It might seem obvious that a group may want to operate on the best available information, but it is the ways to try to achieve such a scenario that Ray shares which may be of most interest in the talk.

How to apply idea meritocracy elsewhere

Can you think of any other scenarios in which operating on the best available belief information by leveraging not only the collected, unbridled insights of a team or organization (and the metadata about those insights), but also incorporating that data through contextually relevant algorithms, could yield useful results?

Consider how the Oneslate system might be used act on collected beliefs and evaluations that are

  1. radically truthful and
  2. radically transparent

by asking the following questions:

  • How you might your team’s or organization’s principles be implemented into algorithms used to provide smart, pertinent suggestions, based on the collected data?
  • Could the Oneslate system provide positive benefit by enabling idea meritocracy in scenarios that matter to you, similar to how the Dot Collector helps Bridgewater Associates?

In the Oneslate system, the processes of

  1. logging, searching, and connecting causally related beliefs
  2. rating and re-rating belief validity,
  3. seeing the population’s 5-bin belief validity rating data along with the temporal 5-bin data, and
  4. zooming out to view an entire modifiable and interlinkable support tree at once

might afford a consideration process similar to the one described in the talk, in which seeing the an entire array of rating data in the Dot Collector at once prompts people to question how they know that their opinions are correct.  Furthermore, the Oneslate bias survey data and statistics derived from the Oneslate dataset may be used to help measure believability and to weigh decisions, similar to processes described in the talk.

Select Quotations

The short (~15 minute) talk is recommended if the above is interesting to you.  The full transcript appears on the talk’s page [0], but particularly salient statements are roughly excerpted below, for reference.  The whole talk is rather topical, so there are a lot of quotes to reflect as follows:

‘Rather than thinking, “I’m right,” I started to ask myself, “How do I know I’m right?”‘

“I wanted to make an idea meritocracy.
- Not an autocracy in which I lead and others follow.
- Not a democracy in which everybody’s points of view were equally valued.
- But…an idea meritocracy where the best ideas would win out.”

“I realized that we would need radical truthfulness and radical transparency.
- People needed to say what they believed and to see everything.
- We literally tape almost all conversations and let everyone see everything.
- We have to let people speak and say what they want.
- I need feedback like that…If I don’t let people express their points of view, our relationship wouldn’t be the same, and if I didn’t make that public for everyone to see, we wouldn’t have an idea meritocracy.
- …For the past 24 year’s that’s how we’ve been operating….Collecting principles, embedding the principles in algorithms, and following the algorithms in parallel with our thinking….the “Dot Collector” that helps us do this…
- Note that everyone gets to express their thinking, including their critical thinking, regardless of their position in the company. Jen, who’s 24 years old and right out of college, can tell me, the CEO, that I’m approaching things terribly.

“This tool helps people both express their opinions and then separate themselves from their opinions to see things from a higher level.
- When Jen and others shift their attentions from inputting their own opinions to looking down on the whole screen, their perspective changes. They see their own opinions as just one of many and naturally start asking themselves, ‘How do I know my opinion is right?’
- That shift in perspective is like going from seeing in one dimension to seeing in multiple dimensions.
- And it shifts the conversation from arguing over our opinions to figuring out objective criteria for determining which opinions are best.

“It watches what all these people are thinking and it correlates that with how they think. And it communicates advice back to each of them based on that.”

“Then it draws the data from all the meetings to create a pointilist painting of what people are like and how they think. And it does that guided by algorithms. Knowing what people are like helps to match them better with their jobs. For example, a creative thinker who is unreliable might be matched up with someone who’s reliable but not creative. Knowing what people are like also allows us to decide what responsibilities to give them and to weigh our decisions based on people’s merits. We call it their believability.”

“This process allows us to make decisions not based on democracy, not based on autocracy, but based on algorithms that take people’s believability into consideration.”

“We do it because it eliminates what I believe to be one of the greatest tragedies of mankind, and that is people arrogantly, naively holding opinions in their minds that are wrong, and acting on them, and not putting them out there to stress test them. And that’s a tragedy. And we do it because it elevates ourselves above our own opinions so that we start to see things through everybody’s eyes, and we see things collectively.”

“Collective decision-making is so much better than individual decision-making if it’s done well. It’s been the secret sauce behind our success. It’s why we’ve made more money for our clients than any other hedge fund in existence and made money 23 out of the last 26 years.”

“So what’s the problem with being radically truthful and radically transparent with each other? People say it’s emotionally difficult. Critics say it’s a formula for a brutal work environment.”
- There’s a part of our brain that would like to know our mistakes and like to look at our weaknesses so we could do better. I’m told that that’s the prefrontal cortex. And then there’s a part of our brain which views all of this as attacks. I’m told that that’s the amygdala.
- It’s been our experience that we can win this battle. We win it as a group. It takes about 18 months typically to find that most people prefer operating this way, with this radical transparency than to be operating in a more opaque environment. There’s not politics, there’s not the brutality of — you know, all of that hidden, behind-the-scenes — there’s an idea meritocracy where people can speak up. And that’s been great. It’s given us more effective work, and it’s given us more effective relationships. But it’s not for everybody. We found something like 25 or 30 percent of the population it’s just not for.

“And by the way, when I say radical transparency, I’m not saying transparency about everything. I mean, you don’t have to tell somebody that their bald spot is growing or their baby’s ugly. So, I’m just talking about the important things.”

“…I’d like you to observe yourself in conversations with others.
- Imagine if you knew what they were really thinking, and
- imagine if you knew what they were really like … and
- imagine if they knew what you were really thinking and what were really like.
- It would certainly clear things up a lot and make your operations together more effective.
- I think it will improve your relationships.

Now imagine that you can have algorithms that will help you gather all of that information and even help you make decisions in an idea-meritocratic way.”

“This sort of radical transparency is coming at you and it is going to affect your life. And in my opinion, it’s going to be wonderful.”