Think Better, Decide Better: Critical Thinking in Business

C.I.S. editorial summary

Julia Galef contrasts the soldier mindset, which defends a position, with the scout mindset, which tries to understand reality accurately. In business, the distinction helps founders and teams notice when loyalty to an idea has begun to outweigh evidence.

Key learning points

• Separate identity from the idea being tested
• Ask what evidence would change your mind
• Reward accurate revision, not only confident advocacy

C.I.S. editorial summary

Margaret Heffernan argues that productive conflict is central to strong thinking. She shows how trusted collaborators who question one another can improve research and decisions, provided disagreement is directed towards the work rather than the person.

Key learning points

• Invite challenge before a decision becomes fixed
• Create roles and routines for rigorous questioning
• Protect people who raise inconvenient evidence

C.I.S. editorial summary

Dan Ariely uses behavioural experiments to show how apparently small features of a choice can influence decisions. Businesses can apply this insight to examine pricing, forms, customer journeys and internal processes—and to recognise their ethical responsibility when designing them.

Key learning points

• Audit the defaults built into important decisions
• Test how framing changes responses
• Do not confuse predictable influence with informed consent

C.I.S. editorial summary

Tricia Wang argues for combining big data with ‘thick data’: close qualitative understanding of people’s lives, motivations and circumstances. For business decisions, numbers become more useful when interpreted alongside observation, conversation and cultural context.

Key learning points

• Combine quantitative patterns with qualitative inquiry
• Investigate outliers rather than deleting them automatically
• Ask whose experience the dataset does not capture

C.I.S. editorial summary

Data journalist Mona Chalabi offers practical questions for evaluating statistics: how the information was collected, what definitions were used and how the figure relates to an appropriate comparison. These habits help businesses resist misleading precision.

Key learning points

• Trace a statistic to its original source
• Check definitions, sample and collection method
• Look for a meaningful denominator or comparison

C.I.S. editorial summary

Philip Tetlock explains why good forecasters remain open-minded, break large questions into smaller parts and revise probabilities as conditions change. The business value is a more disciplined way to discuss uncertain futures without pretending that a forecast is a fact.

Key learning points

• Express uncertainty as a range or probability
• Update forecasts when relevant evidence changes
• Keep records so judgement can be calibrated over time

C.I.S. editorial summary

Emergency manager Jonathan Reimer considers the balance between analysis, experience and intuition when circumstances are difficult. For leaders, the practical lesson is to define what matters, identify what remains unknown and avoid allowing urgency to erase reflection.

Key learning points

• Clarify the decision and the consequence of delay
• Distinguish evidence from intuition and assumption
• Name who decides and who bears the risk

C.I.S. editorial summary

Mariano Sigman and Dan Ariely explore how small-group deliberation can improve collective decisions. The talk suggests that structured conversation can help people find areas of agreement without erasing meaningful differences.

Key learning points

• Use small-group discussion to surface reasoning
• Record minority and uncertain positions
• Design deliberation before asking for consensus

C.I.S. editorial summary

Hans and Ola Rosling demonstrate how people systematically misjudge global conditions and offer habits for correcting dramatic or outdated assumptions. Businesses working across communities and markets need current evidence without flattening local differences.

Key learning points

• Test familiar claims against current evidence
• Beware narratives built only from exceptional events
• Keep global patterns and local variation visible together

C.I.S. editorial summary

Advait Sarkar examines the cognitive trade-offs of using generative AI at work. Faster output may reduce the effort through which people understand a problem, so organisations should design AI use around reflection, verification and accountable human judgement.

Key learning points

• Use AI to generate questions as well as answers
• Verify claims against appropriate sources
• Keep human responsibility visible at every decision point