{
  "version": 1,
  "entries": [
    {
      "slug": "work-project-decisions",
      "title": "Work & project decisions",
      "summary": "Use these evidence-reviewed lenses when a team is choosing a direction, interpreting results, deciding whether to continue, or turning metrics into action.",
      "useWhen": [
        "A project review is being driven by the latest success or failure.",
        "A team keeps investing because too much has already been spent.",
        "A KPI is becoming more important than the goal it was meant to represent.",
        "The team is searching for evidence after already preferring one solution.",
        "A retrospective is quietly rewriting what was knowable, how good the decision was, or how blameworthy the decision-maker now seems."
      ],
      "workflow": [
        "Freeze the information set: what did the team actually know before the latest outcome?",
        "Separate decision-process quality from whether the result happened to be good or bad.",
        "When blame or praise enters the review, separate intention, reasonable belief, controllable risk, causal responsibility, and the eventual outcome.",
        "Write the next increment of cost and expected value without counting already-spent resources as a future benefit.",
        "Name the strategic goal behind each important metric and one way the metric could improve while the goal gets worse.",
        "Specify what evidence would change the preferred plan before gathering another round of supporting evidence."
      ],
      "lenses": [
        {
          "slug": "cognitive-bias-confirmation-bias",
          "question": "What evidence would make us abandon or materially change the preferred explanation?"
        },
        {
          "slug": "cognitive-bias-outcome-bias",
          "question": "Would we rate this decision process the same way if the outcome had gone the other direction?"
        },
        {
          "slug": "cognitive-bias-hindsight-bias",
          "question": "What did our actual pre-outcome forecast or notes say before the result became obvious?"
        },
        {
          "slug": "attribution-bias-moral-luck",
          "question": "Would we assign the same blame or praise if the decision-maker had the same intent, beliefs, and controllable risk but luck produced a different outcome?"
        },
        {
          "slug": "logical-fallacy-escalation-of-commitment",
          "question": "If we had not already invested anything, would we still fund the next step on its future merits?"
        },
        {
          "slug": "cognitive-bias-surrogation",
          "question": "What underlying goal is this metric supposed to represent, and where can the proxy diverge from it?"
        }
      ]
    },
    {
      "slug": "forecasting-future-choices",
      "title": "Forecasting & future choices",
      "summary": "Use these evidence-reviewed lenses when estimating uncertainty, imagining future feelings or preferences, or reviewing forecasts after the outcome is known.",
      "useWhen": [
        "A vivid recent example is dominating a probability estimate.",
        "A broad event looks less likely than the sum of its possible forms.",
        "A current mood, appetite, pain level, craving, or preference is shaping a long-term commitment.",
        "A future event is expected to make life dramatically better or worse for a long time.",
        "The finished outcome now feels much more predictable than it did beforehand."
      ],
      "workflow": [
        "Write the packed event first, then unpack it into mutually exclusive possibilities and compare the totals.",
        "Check a base rate or reference class before using vivid examples as the probability estimate.",
        "Record the current state and the future state you are trying to predict; note where motives, cravings, pain, fear, or arousal may differ.",
        "Forecast emotional intensity and duration separately, including what an ordinary week around the event will contain.",
        "Store the forecast before the outcome so retrospective learning does not depend on reconstructed memory."
      ],
      "lenses": [
        {
          "slug": "probability-bias-subadditivity-effect",
          "question": "Does the total probability change when the same event is unpacked into explicit possibilities?"
        },
        {
          "slug": "heuristic-bias-availability-bias",
          "question": "Are the examples easy to recall because they are common, or because they are vivid, recent, or repeated?"
        },
        {
          "slug": "cognitive-bias-projection-bias",
          "question": "Which part of today's state am I assuming will still describe my future self?"
        },
        {
          "slug": "cognitive-bias-impact-bias",
          "question": "Am I forecasting the focal event while forgetting the rest of ordinary future life?"
        },
        {
          "slug": "self-assessment-hot",
          "question": "Am I predicting choices in a future hot or cold state from a state with different motives, cravings, pain, fear, or arousal?"
        },
        {
          "slug": "cognitive-bias-hindsight-bias",
          "question": "What probability did I actually assign before I learned the outcome?"
        }
      ]
    },
    {
      "slug": "ai-assisted-decisions",
      "title": "AI-assisted decisions",
      "summary": "Use these evidence-reviewed lenses when a chatbot, model, recommendation system, or automated decision aid is influencing what you believe or do.",
      "useWhen": [
        "You are tempted to accept an AI recommendation without checking the underlying evidence.",
        "A fluent, warm, or humanlike interface feels more capable or trustworthy than its tested performance justifies.",
        "The system’s appearance, voice, avatar, or conversational style is shaping what you think it can understand or do.",
        "An early AI score, estimate, or suggested number is becoming the starting point for your own judgment.",
        "You are prompting an AI mainly to strengthen a conclusion you already prefer.",
        "A claim has appeared in several AI outputs and is starting to feel true because it is familiar."
      ],
      "workflow": [
        "Write a provisional judgment, success criterion, or uncertainty range before looking at AI advice when the decision is consequential.",
        "Separate the interface from the capability: list what the system actually needs to know, access, or verify to support the recommendation.",
        "When the AI supplies a number, compare it with an independent estimate, base rate, or reference class instead of adjusting only from the model’s value.",
        "Ask for the strongest counterevidence or alternative explanation, then verify important claims against an independent source rather than another generated paraphrase.",
        "Treat repeated wording as repetition, not independent evidence; trace important claims back to primary or genuinely independent sources.",
        "Record what changed after using AI, what was independently checked, and what trigger would make you reopen the decision."
      ],
      "lenses": [
        {
          "slug": "false-priors-automation-bias",
          "question": "Am I using the automated recommendation as a substitute for checking the evidence I could realistically verify?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Did the AI’s first number become my starting point before I formed an independent estimate?"
        },
        {
          "slug": "availability-heuristic-anthropomorphism",
          "question": "Which humanlike cues are making me infer understanding, intention, empathy, or competence that I have not actually tested?"
        },
        {
          "slug": "human-robot-interaction-form",
          "question": "What capabilities am I inferring from appearance, voice, interface polish, or conversational style rather than observed performance?"
        },
        {
          "slug": "cognitive-bias-confirmation-bias",
          "question": "Did I ask the AI to test my preferred conclusion, or mainly to produce better arguments for it?"
        },
        {
          "slug": "truth-judgment-illusory-truth-effect",
          "question": "Does this claim feel more credible because I have encountered it repeatedly, or because I verified independent evidence for it?"
        }
      ]
    },
    {
      "slug": "project-estimation-delivery",
      "title": "Project estimation & delivery",
      "summary": "Use these evidence-reviewed lenses when setting a deadline, estimating effort, discussing delivery risk, or learning from a project that finished later than expected.",
      "useWhen": [
        "A deadline is being built from a detailed plan without checking how long similar work actually took.",
        "An early target, budget, or rough estimate is pulling later discussion toward the same number.",
        "A team is debating one precise date even though important dependencies and unknowns remain.",
        "A project is already late and the new estimate is again starting from the ideal plan.",
        "Delivery risk is discussed as one broad feeling instead of explicit ways the plan could slip.",
        "After delivery, the final outcome is changing what people remember about the original estimate."
      ],
      "workflow": [
        "Start with comparable completed work. Write down what similar tasks actually took before refining the current plan.",
        "Check whether a target, budget, or early rough number became an anchor. Build an independent estimate when possible before reconciling the two.",
        "Give a useful range and explain what would push delivery toward the earlier or later end.",
        "Unpack the main ways the plan can slip instead of hiding all uncertainty inside one confidence number.",
        "Record the estimate, assumptions and important unknowns before work starts so the later review has a real baseline.",
        "When the plan changes, judge the next step on future cost and value rather than on how much has already been spent."
      ],
      "lenses": [
        {
          "slug": "egocentric-bias-planning-fallacy",
          "question": "What happened on the most comparable completed work, and why should this case be faster or slower?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Which early number is shaping this estimate, and what would we estimate if we had not seen it first?"
        },
        {
          "slug": "probability-bias-subadditivity-effect",
          "question": "Does the risk estimate change when we unpack the main ways the project could be delayed?"
        },
        {
          "slug": "heuristic-bias-availability-bias",
          "question": "Are we using a vivid recent project as the baseline because it is representative, or simply because it is easy to remember?"
        },
        {
          "slug": "cognitive-bias-hindsight-bias",
          "question": "What did the original estimate and assumptions actually say before we knew the delivery result?"
        },
        {
          "slug": "logical-fallacy-escalation-of-commitment",
          "question": "If we were deciding only about the remaining work today, would we still choose the same next step?"
        }
      ]
    },
    {
      "slug": "checking-claims-misinformation",
      "title": "Checking claims & misinformation",
      "summary": "Use these evidence-reviewed lenses when deciding whether a repeated claim is trustworthy, checking a correction, or testing an explanation against plausible alternatives.",
      "useWhen": [
        "A claim feels credible because you have seen it in many places, but those places may be repeating the same source.",
        "You are searching mainly for evidence that supports a conclusion you already prefer.",
        "A test supports the leading explanation, but plausible alternatives would predict the same result.",
        "One vivid example is shaping your judgment more than broader evidence.",
        "A false claim has been corrected, but the old explanation still appears in later reasoning.",
        "Someone resists a correction and the reaction is immediately described as a backfire effect."
      ],
      "workflow": [
        "Write the exact claim you are checking. Separate the claim itself from your opinion about the person or source sharing it.",
        "Trace repeated versions back to genuinely independent sources. Ten repetitions of one source are still one source.",
        "Write what evidence would make the preferred claim weaker or wrong before gathering another round of support.",
        "List at least one plausible alternative explanation. For an important test, predict the result under both explanations and prefer observations where their predictions differ.",
        "Use the same evidence-quality standard for results that support and challenge the preferred explanation.",
        "If a correction is needed, state the corrected information clearly and provide the best supported alternative explanation when one is available.",
        "After a correction, distinguish incomplete updating from backfire. Ask whether belief in the false claim actually became stronger or whether some influence simply remained."
      ],
      "lenses": [
        {
          "slug": "cognitive-bias-confirmation-bias",
          "question": "Am I using the same evidence standard for information that supports and challenges the claim?"
        },
        {
          "slug": "confirmation-bias-congruence-bias",
          "question": "Would this test distinguish the preferred explanation from plausible alternatives, or would they predict the same result?"
        },
        {
          "slug": "truth-judgment-illusory-truth-effect",
          "question": "Does this feel true because it was independently verified, or because I have encountered the same claim repeatedly?"
        },
        {
          "slug": "heuristic-bias-availability-bias",
          "question": "Is the example easy to recall because it is representative, or because it is vivid, recent, emotional, or repeated?"
        },
        {
          "slug": "memory-bias-continued-influence-effect",
          "question": "After the correction, am I still using part of the old information when explaining or judging the situation?"
        },
        {
          "slug": "confirmation-bias-backfire-effect",
          "question": "Did belief in the corrected false claim actually become stronger, or am I calling disagreement or incomplete updating a backfire?"
        }
      ]
    },
    {
      "slug": "comparing-plans-pricing",
      "title": "Comparing plans & pricing",
      "summary": "Use these evidence-reviewed lenses when comparing subscription tiers, product plans, vendor offers or recommendation menus where the way options are arranged may change what looks attractive.",
      "useWhen": [
        "A three-tier pricing table makes one plan suddenly look like the obvious value choice.",
        "An extra option is clearly worse than one plan but still changes how the stronger options are compared.",
        "One plan is already selected or renews automatically unless the user changes it.",
        "A list price, target budget or recommended price is becoming the reference point for the comparison.",
        "Equivalent features or outcomes are described differently across plans, making direct comparison difficult."
      ],
      "workflow": [
        "List the serious options and the attributes that matter to your goal before using badges, highlights or recommended labels.",
        "Remove any suspected decoy and compare the remaining options again. If your preference changes, inspect what contrast the extra option created.",
        "Identify the no-action outcome separately. A default can influence choice even when no decoy is present.",
        "Hide or replace the starting price, target or recommendation when practical and make an independent estimate of value before reconciling it with the displayed number.",
        "Rewrite important attributes in matched units and neutral language so equivalent differences are easy to compare.",
        "Choose on expected value and fit to the actual need. Conversion, popularity and a 'recommended' badge are not substitutes for the decision criteria."
      ],
      "lenses": [
        {
          "slug": "framing-effect-decoy-effect",
          "question": "Does removing the inferior or strategically positioned option change my preference between the remaining plans?"
        },
        {
          "slug": "framing-effect-default-effect",
          "question": "Which plan applies if I do nothing, and is that automatic outcome being mistaken for preference?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Which displayed price, budget or recommendation became the starting point for my value judgment?"
        },
        {
          "slug": "framing-effect-core",
          "question": "Are equivalent features, gains, losses or rates described differently across the options?"
        }
      ]
    },
    {
      "slug": "defaults-settings-choice-architecture",
      "title": "Defaults, settings & choice architecture",
      "summary": "Use these evidence-reviewed lenses when a form, product, policy or system decides what happens if a person does nothing, or when an existing setting is difficult to reconsider.",
      "useWhen": [
        "A checkbox, permission, subscription or contribution is already selected before the user makes a choice.",
        "A product team is deciding what the starting settings should be for a new user.",
        "People rarely change a setting and the team is treating that as proof that the setting is preferred.",
        "An old workflow or service remains in place even though alternatives now exist.",
        "A recommendation, suggested number or wording may be influencing the choice alongside the default."
      ],
      "workflow": [
        "Write down what happens if the person takes no action. Make the default explicit before discussing conversion or uptake.",
        "Separate the designed default from the existing status quo. They can be the same option, but they do not have to be.",
        "Make important alternatives visible and keep switching reasonably easy. Friction can create persistence without strong preference.",
        "When possible, compare the design with active choice or another default while keeping the underlying options the same.",
        "Check whether wording, recommended values or starting numbers are also changing the decision. Do not attribute every difference to the default.",
        "Evaluate whether the resulting choice serves the user's goals. Uptake alone is not enough to establish welfare or informed preference."
      ],
      "lenses": [
        {
          "slug": "framing-effect-default-effect",
          "question": "What happens automatically if the person does nothing, and how much does that pre-selection change uptake?"
        },
        {
          "slug": "prospect-theory-status-quo-bias",
          "question": "Is the current option getting extra weight simply because it is already in place?"
        },
        {
          "slug": "framing-effect-core",
          "question": "Would the choice change if the same outcomes were described with an equivalent gain, loss or attribute frame?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Did a suggested number, threshold or starting value become the reference point for the decision?"
        }
      ]
    },
    {
      "slug": "presenting-risk-options",
      "title": "Presenting risk & options",
      "summary": "Use these evidence-reviewed lenses when a report, interface, model, or recommendation is presenting numbers and choices that other people will use to decide.",
      "useWhen": [
        "The same outcome can be described as a gain, a loss, a success rate, or a failure rate.",
        "A reference point determines whether the same change is experienced as gaining something or losing something.",
        "One prominent number appears before people form their own estimate.",
        "A broad risk category hides several different ways the outcome could happen.",
        "A vivid example or recent incident is being used next to statistical evidence.",
        "An AI interface chooses the wording, score, ordering, or examples that a person sees before deciding."
      ],
      "workflow": [
        "Write the underlying outcomes, quantities, and probabilities in a neutral form before choosing presentation language.",
        "State the reference point explicitly and compare matched positive and negative changes. When possible, also show the absolute outcomes rather than only the gain or loss from the reference point.",
        "Create matched gain and loss descriptions for important risk choices. Check whether the decision changes even though the underlying outcomes do not.",
        "Identify the first numerical reference point. When practical, collect an independent estimate before revealing it or compare against several relevant references.",
        "Unpack broad risks into mutually exclusive possibilities and compare the total with the original packed estimate.",
        "Separate illustrative examples from frequency evidence. A memorable case can help explain a risk without representing how common it is.",
        "For consequential interfaces or reports, test alternative presentations and measure the resulting choices instead of assuming one wording is neutral."
      ],
      "lenses": [
        {
          "slug": "framing-effect-core",
          "question": "Would the choice change if the same outcomes were presented with an equivalent gain, loss, or neutral description?"
        },
        {
          "slug": "prospect-theory-loss-aversion",
          "question": "What is the reference point, and are equivalent losses receiving more weight than comparable gains in this decision?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Which number is shown first, and is it pulling later estimates toward itself?"
        },
        {
          "slug": "probability-bias-subadditivity-effect",
          "question": "Does the total risk estimate change when the same outcome is unpacked into explicit possibilities?"
        },
        {
          "slug": "heuristic-bias-availability-bias",
          "question": "Is a vivid example affecting the estimate because it is representative, or mainly because it is easy to recall?"
        }
      ]
    },
    {
      "slug": "reviewing-kpis-proxy-metrics",
      "title": "Reviewing KPIs & proxy metrics",
      "summary": "Use these evidence-reviewed lenses when a team is using scores, dashboards, targets, benchmarks, or AI evaluations to represent a broader objective.",
      "useWhen": [
        "A KPI is improving, but people disagree about whether the underlying service, product, learning, safety, or business outcome is actually better.",
        "A target is tied to incentives and teams have found ways to improve the number that do not clearly improve the goal.",
        "A dashboard or benchmark is becoming the main language of the review while the underlying objective is harder to discuss.",
        "A benchmark or model score is being treated as the main evidence that an AI system is useful in real work.",
        "A successful result is being used to justify the metric or target even though the quality of the measurement and decision process was never tested.",
        "Teams mainly look for examples that support the current KPI and rarely ask what evidence would show that the measure is a poor proxy."
      ],
      "workflow": [
        "Write the underlying objective in ordinary language before opening the dashboard. Describe what success means without using the KPI name.",
        "For each important measure, list what it captures directly, what it only approximates, and at least one important dimension it misses.",
        "Ask how someone could improve the number while making the real objective worse. If that path is realistic, add a guardrail, companion measure, validation check, or narrative review.",
        "Identify the first target, benchmark, baseline, or score shown in the review. Rebuild important estimates from independent evidence before letting that number become the reference point.",
        "Write what evidence would make you change or retire the metric before the next review. Search for that evidence, not only for examples that defend the current scorecard.",
        "Judge the metric design and the eventual outcome separately. A good outcome does not prove the proxy was well chosen, and a bad outcome does not prove every part of the measurement system was wrong.",
        "For AI benchmarks and automated ratings, validate against representative real tasks and human outcomes instead of assuming one convenient score is the product objective. Check the measurement process separately when data coverage, sampling, calibration, labels, or exclusions may be systematically distorted."
      ],
      "lenses": [
        {
          "slug": "cognitive-bias-surrogation",
          "question": "Are we treating the measure as evidence about the objective, or have we started treating the measure as the objective itself?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Which target, benchmark, baseline, or first score is shaping later judgments before we build an independent estimate?"
        },
        {
          "slug": "cognitive-bias-confirmation-bias",
          "question": "What evidence would show that this KPI is a poor proxy, and have we actively looked for it?"
        },
        {
          "slug": "cognitive-bias-outcome-bias",
          "question": "Are we judging the quality of the metric and decision process mainly from whether the final result happened to be good or bad?"
        }
      ]
    },
    {
      "slug": "comparing-past-present",
      "title": "Was the past really better?",
      "summary": "Use these evidence-reviewed lenses when a personal memory or broad story about decline is being used to compare the present with an earlier period.",
      "useWhen": [
        "Someone says a profession, product, institution, city, community, or society used to be better, but the indicators and comparison years are unclear.",
        "A remembered project, job, school period, trip, relationship, or community feels much better now than it felt while it was happening.",
        "Current problems are vivid and detailed while the negative emotional intensity of past problems feels weaker.",
        "A few personal memories are being used as evidence for a broad historical trend.",
        "Nostalgia or dissatisfaction with the present is starting to replace measurable comparison."
      ],
      "workflow": [
        "Define the claim before debating it. Write what exactly was better or worse, for whom, where, and between which years.",
        "Separate personal event memory from population or system trends. A remembered experience can be useful evidence about your experience without representing an era.",
        "Look for contemporaneous records from both periods: surveys, logs, prices, defect rates, service levels, health or safety measures, diaries, ratings, or other domain-relevant data.",
        "For a remembered event, compare later recollection with records made during the experience when those records exist.",
        "Separate remembered facts from current emotional intensity. Ask whether negative feelings connected with the old experience may have softened over time.",
        "Look for indicators that improved, worsened, and stayed stable. Avoid forcing a mixed historical record into one global better-or-worse verdict.",
        "State what cannot be determined when comparable historical evidence is weak. Memory can be meaningful without being a complete measurement system."
      ],
      "lenses": [
        {
          "slug": "cognitive-bias-declinism",
          "question": "Is a broad story of decline being asserted without a clearly defined indicator, population, and historical comparison?"
        },
        {
          "slug": "memory-bias-rosy-retrospection",
          "question": "Is a specific past experience remembered more positively now than it was experienced or recorded at the time?"
        },
        {
          "slug": "memory-bias-fading-affect-bias",
          "question": "Could the emotional intensity of negative past events have faded faster than positive affect, changing how the period feels in comparison with the present?"
        }
      ]
    },
    {
      "slug": "continue-change-stop-project",
      "title": "Continue, change, or stop a project",
      "summary": "Use these evidence-reviewed lenses when a project has disappointing results and the next decision is whether to invest more, change direction, or stop.",
      "useWhen": [
        "Past spending is the strongest argument for approving the next budget or milestone.",
        "Stopping feels like accepting or making a loss real, even before the remaining future options are compared.",
        "The person who chose the original plan is also deciding whether it should continue.",
        "A project is described as too close to completion to stop, but the remaining value and cost are unclear.",
        "A target, original business case, or early estimate is still shaping the review after the evidence changed.",
        "An AI or external adviser recommends continuing and the recommendation is starting to replace an independent review."
      ],
      "workflow": [
        "Separate past costs from the next decision. Write the remaining costs, expected future value, important risks, and realistic alternatives from today forward.",
        "Name the reference point that makes stopping or changing direction feel like a loss. Distinguish that prospective loss from money or time that is already irrecoverable.",
        "Describe what useful completion actually produces. Being close to finished can matter when completion has future value, but percentage complete is not value by itself.",
        "Rebuild the current estimate from relevant evidence instead of adjusting only from the original budget, target, or deadline.",
        "Check ownership pressure. Ask someone who did not make the original decision to review the next commitment using the same evidence.",
        "Write continue, change, and stop criteria before the next result arrives. Include what evidence would trigger each option.",
        "After the outcome, review whether the process followed those criteria separately from whether the final result happened to be good or bad."
      ],
      "lenses": [
        {
          "slug": "cognitive-bias-sunk-cost-effect",
          "question": "Which past costs are irrecoverable, and would they change what we choose if we evaluated only the future options?"
        },
        {
          "slug": "prospect-theory-loss-aversion",
          "question": "Is stopping being evaluated as a prospective loss from the current reference point, separately from the sunk costs already paid?"
        },
        {
          "slug": "logical-fallacy-escalation-of-commitment",
          "question": "Are setbacks leading us to commit more resources without reopening whether this course still deserves the next investment?"
        },
        {
          "slug": "cognitive-bias-anchoring-effect",
          "question": "Which original target, budget, valuation, or deadline is still pulling the current judgment toward it?"
        },
        {
          "slug": "egocentric-bias-planning-fallacy",
          "question": "What does comparable completed work say about the cost and time still required from today?"
        },
        {
          "slug": "cognitive-bias-confirmation-bias",
          "question": "What evidence would make us stop or materially change the project, and have we actively looked for it?"
        },
        {
          "slug": "cognitive-bias-outcome-bias",
          "question": "Would we rate the quality of today’s continue-or-stop process the same way if the eventual outcome went the other direction?"
        }
      ]
    }
  ]
}