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  1. Last 7 days
  2. Nov 2022
    1. https://commoncog.com/

      If you're:<br><br>- An independent consultant<br>- A systems thinker<br>- Trying to change organizations<br>- Interested in theory & practice<br><br>Then you'll love CommonCog

      — Tom Critchlow (@tomcritchlow) November 9, 2022
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    1. Nobody ever says rubber ducky debugging involves writing memos to your preferred duck, after all.

      Seemingly both rubber duck debugging and casual conversations with acquaintances would seem to be soft forms of diffuse thinking which may help one come to a heuristic-based decision or realization.

      These may be useful, but should also be used in combination with more logical, system two forms of decision making. (At least not in the quick, notice the problem sort of issues in which one may be debugging.)

  3. Oct 2022
    1. Boosting Human Decision‑making with AI‑Generated Decision Aids

      This is what I've learned from the research. Basically, to make better decisions 1. one needs to have a lot of data about the thing 2. he/she should define the parameters according to which the procedural instructions will the made in-order to make decision. 3. one should be aware of the cognitive biases while making a decision

      For Example- * suppose you are trying to find a college 1. Gather data about the colleges 2. compare the colleges on the parameters you've set 1. like admission fees, companies visiting, average or highest package offered 3. And make sure that you are aware of cognitive biases

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    1. The nature of physics problem-solvingBelow are 29 sets of questions that students and physicists need to ask themselves during the research process. The answers at each step allow them to make the 29 decisions needed to solve a physics problem. (Adapted from reference 33. A. M. Price et al., CBE—Life Sci. Edu. 20, ar43 (2021). https://doi.org/10.1187/cbe.20-12-0276.)A. Selection and planning1. What is important in the field? Where is the field heading? Are there advances in the field that open new possibilities?2. Are there opportunities that fit the physicist’s expertise? Are there gaps in the field that need solving or opportunities to challenge the status quo and question assumptions in the field? Given experts’ capabilities, are there opportunities particularly accessible to them?3. What are the goals, design criteria, or requirements of the problem solution? What is the scope of the problem? What will be the criteria on which the solution is evaluated?4. What are the important underlying features or concepts that apply? Which available information is relevant to solving the problem and why? To better identify the important information, create a suitable representation of core ideas.5. Which predictive frameworks should be used? Decide on the appropriate level of mechanism and structure that the framework needs to be most useful for the problem at hand.6. How can the problem be narrowed? Formulate specific questions and hypotheses to make the problem more tractable.7. What are related problems or work that have been seen before? What aspects of their problem-solving process and solutions might be useful?8. What are some potential solutions? (This decision is based on experience and the results of decisions 3 and 4.)9. Is the problem plausibly solvable? Is the solution worth pursuing given the difficulties, constraints, risks, and uncertainties?Decisions 10–15 establish the specifics needed to solve the problem.10. What approximations or simplifications are appropriate?11. How can the research problem be decomposed into subproblems? Subproblems are independently solvable pieces with their own subgoals.12. Which areas of a problem are particularly difficult or uncertain in the solving process? What are acceptable levels of uncertainty with which to proceed at various stages?13. What information is needed to solve the problem? What approach will be sufficient to test and distinguish between potential solutions?14. Which among the many competing considerations should be prioritized? Considerations could include the following: What are the most important or most difficult? What are the time, materials, and cost constraints?15. How can necessary information be obtained? Options include designing and conducting experiments, making observations, talking to experts, consulting the literature, performing calculations, building models, and using simulations. Plans also involve setting milestones and metrics for evaluating progress and considering possible alternative outcomes and paths that may arise during the problem-solving process.B. Analysis and conclusions16. Which calculations and data analysis should be done? How should they be carried out?17. What is the best way to represent and organize available information to provide clarity and insights?18. Is information valid, reliable, and believable? Is the interpretation unbiased?19. How does information compare with predictions? As new information is collected, how does it compare with expected results based on the predictive framework?20. If a result is different from expected, how should one follow up? Does a potential anomaly fit within the acceptable range of predictive frameworks, given their limitations and underlying assumptions and approximations?21. What are appropriate, justifiable conclusions based on the data?22. What is the best solution from the candidate solutions? To narrow down the list, decide which of those solutions are consistent with all available information, and which can be rejected. Determine what refinements need to be made to the candidate solutions. For this decision, which should be made repeatedly throughout the problem-solving process, the candidate list need not be narrowed down to a single solution.23. Are previous decisions about simplifications and predictive frameworks still appropriate in light of new information? Does the chosen predictive framework need to be modified?24. Is the physicist’s relevant knowledge and the current information they have sufficient? Is more information needed, and if so, what is it? Does some information need to be verified?25. How well is the problem-solving approach working? Does it need to be modified? A physicist should reflect on their strategy by evaluating progress toward the solution and possibly revising their goals.26. How good is the chosen solution? After selecting one from the candidate solutions and reflecting on it, does it make sense and pass discipline-specific tests for solutions to the problem? How might it fail?Decisions 27–29 are about the significance of the work and how to communicate the results.27. What are the broader implications of the results? Over what range of contexts does the solution apply? What outstanding problems in the field might it solve? What novel predictions can it enable? How and why might the solution be seen as interesting to a broader community?28. Who is the audience for the work? What are the audience’s important characteristics?29. What is the best way to present the work to have it understood and to have its correctness and importance appreciated? How can a compelling story be made of the work?
    2. Wieman, Carl. “How to Become a Successful Physicist.” Physics Today 75, no. 9 (September 2022): 46–52. https://doi.org/10.1063/PT.3.5082

      The details here are also good in teaching almost all areas of knowledge, particularly when problem solving is involved.

      How might one teach the practice of combinatorial creativity?

    3. An adviser should have their students explicitly practice decisions 25 and 26, test their solutions, and try to come up with the ways their decisions could fail, including alternative conclusions that are not the findings that they were hoping for. Thinking of such failure modes is something that even many experienced physicists are not very good at, but our research has shown that it can be readily learned with practice.

      To help fight cognitive bias, one should actively think about potential failure modes of one's decisions and think about alternative conclusions which aren't part of the findings one might have hoped for. Watching out for these can dramatically help increase solution spaces and be on the watch out for innovative alternate or even better solutions.

    4. The third and probably most serious difficulty in making good reflective decisions is confirmation bias.

      Confirmation bias can be detrimental when making solid reflective decisions.

    5. To be a successful physicist requires mastering how to make all 29 decisions, but the reflection decisions (decisions 23–26) are arguably the most difficult to learn.

      Of the 29 problem solving decisions identified as important the three "reflection decisions" (23-26 in the list) may be the most difficult to learn as they require metacognition and self-evaluation.

    6. My research group interviewed some 50 skilled scientists and engineers (“experts”), including physicists, on how they solved authentic problems in their discipline. We analyzed the interviews in terms of the decisions made during the solving process. Decisions were defined as instances when an expert selected between competing alternatives before taking some action. To my surprise, we found that the same set of 29 decisions occurred over and over (see the box on page 50). Nearly all of them showed up in every interview, and they essentially defined the problem-solving process.3

      Though interviews with scientists and engineers, researchers have identified a list of 29 commonly occurring decisions made during problem solving processes.

  4. Sep 2022
    1. https://thehill.com/homenews/senate/3641225-mcconnell-throws-shade-on-grahams-proposed-national-abortion-ban/

      I've recently run across a few examples of a pattern that should have a name because it would appear to dramatically change the outcomes. I'm going to term it "decisions based on possibilities rather than realities". It's seen frequently in economics and politics and seems to be a form of cognitive bias. People make choices (or votes) about uncertain futures, often when there is a confluence of fear, uncertainty, and doubt, and these choices are dramatically different than when they're presented with the actual circumstances in practice.

      A recent example was a story about a woman who was virulently pro-life who when presented with a situation required her to switch her position to pro-choice.

      Another relates to choices that people want to make about where their children might go to school versus where they actually send them, and the damage this does to public education.

      Let's start collecting examples of these quandaries at all levels of making choices in the real world.


      What is the relationship to this with the mental exercise of "descending into the particular"?

      Does this also potentially cause decision fatigue in cases of voting spaces when constituents are forced to vote for candidates on thousands of axes which they may or may not agree with?

  5. Aug 2022
  6. Jul 2022
    1. A “razor” is a rule of thumb that simplifies decision making. The most powerful razors I’ve found:
    1. 5.10 Believability weight your decision making.

      5.10 Believability weight your decision making.

    2. 5.1 Recognize that 1) the biggest threat to good decision making is harmful emotions, and 2) decision making is a two-step process (first learning and then deciding).

      5.1 Recognize that 1) the biggest threat to good decision making is harmful emotions, and 2) decision making is a two-step process (first learning and then deciding).

  7. Jun 2022
    1. By dropping or reducing or postponing the least importantparts, we can unblock ourselves and move forward even when timeis scarce.

      When working on a project, to stave off potential procrastination on finishing, one should focus on the minimum viable version and finish that. They can then progressively enhance portions and add on addition pieces which may be beneficial or even nice to have.

      Spending too much time on the things that sound nice or that one "might want to have" in the future will be the death of the thing.

      link to: - you ain't gonna need it - bikeshedding for procrastination

      questions: - Does the misinterpreted-effort hypothesis play a role in creating our procrastination and/or lead to decision fatigue?

  8. Apr 2022
  9. Mar 2022
    1. “Scarcity: WhyHaving Too Little Means So Much” (2013) by Mullainathan andShafir. They investigate how the experience of scarcity has cognitiveeffects and causes changes in decision-making processes.

      I'm reminded of a reference recently to Republicans being upset that poor people of color would "waste" their money on frivolities like manicures and fake fingernails instead of on food or other necessities. How might this tie into the argument made in this book?

  10. Feb 2022
    1. Even though results of these studies are currently under intensescrutiny and have to be taken with a grain of salt (Carter andMcCullough 2014; Engber and Cauterucci 2016; Job, Dweck andWalton 2010), it is safe to argue that a reliable and standardisedworking environment is less taxing on our attention, concentration

      and willpower, or, if you like, ego. It is well known that decision-making is one of the most tiring and wearying tasks...

      Having a standardized and reliable working environment or even workflow can be less taxing on our attention, our concentration, and our willpower leaving more energy for making decisions and thinking which can have a greater impact.

      Does the fact that the relative lack of any decision making about what to see or read next seen in doomscrolling underlie some of the easily formed habit of the attention economy? Not having to actively decide what to read next combined with the random rewards of interesting tidbits creating a sense of flow is sapping not our mental energy, but our time. How can we better design against this?

  11. Jan 2022
  12. Nov 2021
    1. Many decisions are reversible, two-way doors. Those decisions can use a light-weight process. Most decisions should probably be made with somewhere around 70 percent of the information you wish you had. Some decisions are consequential and irreversible or nearly irreversible -- one-way doors -- and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don't like what you see on the other side, you can't get back to where you were before. But most decisions aren't like that -- they are changeable, reversible -- they're two-way doors. If you've made a suboptimal two-way door decision, you don't have to live with the consequences for that long. You can reopen the door and go back through.

      Reversible decisions can be made with less information / certainty

    1. Dr. Thomas Wilckens. (2021, October 31). JCVI facing calls from within for greater transparency over decision-making https://buff.ly/3GwVqCZ JCVI has been criticised for failing to publish detailed minutes, modelling and analysis behind its decision to advise vaccinating all over-16s in Britain #covid19 #coronavirus https://t.co/nWbnvci7LI [Tweet]. @Thomas_Wilckens. https://twitter.com/Thomas_Wilckens/status/1454798820156530689

  13. Oct 2021
    1. “Speed kills.” If you are able to be nimble, assess the ever-changing environment, and adapt quickly, you’ll always carry the advantage over any opponents. Start applying the OODA Loop to your day-to-day decisions and watch what happens. You’ll start to notice things that you would have been oblivious to before. Before jumping to your first conclusion, you’ll pause to consider your biases, take in additional information, and be more thoughtful of consequences.

      In che modo si può applicare il modello OODA Loop nella vita quotidiana?

      Semplicemente applicando ad ogni nostra decisione le fasi previste dal modello, rendendo questo processo una abitudine riusciremo ad essere sempre più veloci nell'eseguirlo e questo ci darà la velocità necessaria per sopravvivere e vincere.

    1. Team syntegrity and democratic group decision making: theory and practice

      Team Syntegrity

      Stafford Beer created Team Syntegrity as a methodology for social interaction that predisposes participants towards shared agreement among varied and sometimes conflicting interests, without compromising the legitimate claims and integrity of those interests. This paper outlines the methodology and the underlying philosophy, describing several applications in a variety of countries and contexts, indicating why such an approach causes us to re-think more traditional approaches to group decision processes, and relating Team Syntegrity to other systems approaches.

      Shared by Kirby Urner in the Trimtab Book Club

  14. Sep 2021
  15. Aug 2021
  16. Jul 2021
    1. To the extentthat people accommodate themselves to the faceless inflexibility ofplatforms, they will become less and less capable of seeing thevirtues of institutions, on any scale. One consequence of thataccommodation will be an increasing impatience withrepresentative democracy, and an accompanying desire to replacepolitical institutions with platform-based decision making:referendums and plebiscites, conducted at as high a level as possible(national, or in the case of the European Union, transnational).Among other things, these trends will bring, in turn, theexploitation of communities and natural resources by people whowill never see or know anything about what they are exploiting. !escope of local action will therefore be diminished, and will comeunder increasing threat of what we might call, borrowing a phrasefrom Einstein, spooky action at a distance.

      This fits in line with my thesis to make corporations and especially corporate executives and owners be local, so that they can see the effect that their decisions are having.

  17. Jun 2021
    1. your goal cannot be to follow orders in order to get a higher grade, instead you are free to listen, consider things, ignore ideas, or ask more honest questions of your readers. You are now free to make your own decisions on your writing. 

      Labor-based grading in writing allows students to listen and adjust to comments which gives them greater freedom and autonomy in both their learning process as well as their writing.

      Ideally, in a system like this, a shorter feedback loop of commentary and readjustment may also help to more carefully hone their skills versus potentially hitting a plateau after which it's more difficult to improve.

    1. V Shah, A. S., Gribben, C., Bishop, J., Hanlon, P., Caldwell, D., Wood, R., Reid, M., McMenamin, J., Goldberg, D., Stockton, D., Hutchinson, S., Robertson, C., McKeigue, P. M., Colhoun, H. M., & McAllister, D. A. (2021). Effect of vaccination on transmission of COVID-19: An observational study in healthcare workers and their households [Preprint]. Public and Global Health. https://doi.org/10.1101/2021.03.11.21253275

    1. better “decision hygiene” such as designating an observer for group decisions, to prevent common biases and noisy judgments. For example, they can ensure that participants in a team reach independent assessments before coming together as a group to aggregate their decisions.

      Approaches for decreasing noise in decision making

  18. May 2021
    1. Career decision making involves so much uncertainty that it’s easy to feel paralysed. Instead, make some hypotheses about which option is best, then identify key uncertainties: what information would most change your best guess?

      We tend to think that uncertainties can't be weighted in our decision-making, but we bet on uncertainties all the time. Rather than throw your hands up and say, "I don't have enough information to make a call", how can we think deliberately about what information would reduce the uncertainty?

  19. Apr 2021
  20. Mar 2021
    1. Chapman, G. B., & Coups, E. J. (2006). Emotions and preventive health behavior: Worry, regret, and influenza vaccination. Health Psychology: Official Journal of the Division of Health Psychology, American Psychological Association, 25(1), 82–90. https://doi.org/10.1037/0278-6133.25.1.82

    1. Baker, C. M., Campbell, P. T., Chades, I., Dean, A. J., Hester, S. M., Holden, M. H., McCaw, J. M., McVernon, J., Moss, R., Shearer, F. M., & Possingham, H. P. (2020). From climate change to pandemics: Decision science can help scientists have impact. ArXiv:2007.13261 [Physics]. http://arxiv.org/abs/2007.13261