Q. Do you offer professional financial advice?

A. Categorically not. I do not provide personal investment advice, and I am not a qualified licensed investment advisor. All information found here, including any ideas, opinions, views, predictions, forecasts, commentaries, suggestions, or stock picks, expressed or implied herein, are for educational purposes only and should not be construed as investment advice. While the information provided is believed to be accurate, it may include errors or inaccuracies.

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Q. How do I know if the answers are reliable?

A. We use a number of methods as follows:

• Every answer shows the top five sources used at the Evidence level and are graded on a scale of 1 to 5 where 5 is the maximum. Generally, shown sources score above 4, unless the topic is new or obscure.
• A hidden generic prompt instructs Alexis on what to do, what not to do, and how to behave, in answering every question.
• The system uses multi-methods in combination with each other which considerably reduces the chance of outputting wrong answers.
• In background, Alexis self-audits her answers from twelve perspectives, at the end of her analysis and offers recommendations for improvement. We regularly watch for new recommendations and add these to increase answer quality.
• We recently supplemented the self-audit and replaced it on the live-service with machine learning methods that create Explainable AI. The AI's response can be found for every Question answered behind the Methods button on every Our World page.
• We constantly test the answers to our own questions and have reached a point now where the Explainable AI is no longer suggesting changes to our basic system. It is now only suggesting greater human input, which is already available, and a real-time connection which we wait for from OpenAI.
• Humans are biased and hallucinate too and cannot always explain how they arrived at an answer. We believe the above methods lead to very reliable results, with only small errors such as naming recently retired or dead people as still living, due to the AI's cutoff date. Please let us know if you spot any hallucinations and we will do our best to eliminate them in the future.

Q. How does this system reduce the need to be formally trained in foresight, systems, design, and critical thinking methods?

A. Not everyone has the time, money, or inclination to go to college to learn these techniques. Instead, we train people through the built-in critical thinking tools and through the use of Explainable AI to offer more understanding of which methods are being used to derive Alexis's answers.

• There is also no way anyone can learn and regularly practice the nearly 700 integrated methods and 2,000 future questions without a digital aid like this one.
• Today's educational institutions cannot turn out sufficient futurists to cover the many millions of jobs that require forward decision making today. We appreciate, recognize the need for, and support, their efforts to train professional future thinkers but we do not believe this is enough.
• It is our view that the benefit of helping many millions of lay decision-makers, who have urgent needs for better decisions, is far better than limiting this learning to the privileged few, and that encouraging critical thinking on ready-made plans is a far better use of their time.
• We will shortly add a foresight, systems, design, and critical thinking course here to add to members' learning needs, and eventually professional certification, further closing this gap in knowledge.

Q. Why does the Evidence analysis repeat itself?

A. That is because each chapter simultaneously stands alone and feeds forward (in an embedded neural network) to the next chapter in the analysis. This has advantages and disadvantages: Firstly, the system uses the number of mentions to assess the relative strengths of each and as part of prioritizing its proposed strategy. Second, it means each chapter can be standalone in this click-and-point presentation format and allow one to dip in, and out, as necessary.

But repetition makes it longer and harder to read as a full analysis. We know that, but tests tell us that by removing the repetition we are breaking system thinking as a whole, and returning to seeing the world only in parts. We believe that whole system thinking holds much more promise, in an uncertain world, to remain agile and resilient in the face of accelerating change.

Q. Does the AI hallucinate and/or produce false information?

A. Yes, it can. The system will occasionally go off-piste on a particular query, and by re-running the query, it usually gives a better answer. Most times, it gets its formatting wrong, rather than the answer. We have endeavored to restrain these off-ramps and deviations. You can help too by limiting the number of words input in your query and making each count. A little time spent making your query concise and on point will pay big dividends in the AI's answers.

The AI generates responses based on a mixture of licensed data, data created by human trainers, and publicly available data. In the case of specific prompts, the model was trained on a diverse range of internet text. It does not know specifics about which documents were in its training set or have the ability to access any classified, confidential, proprietary, or personal data.

The potential also exists for PreEmpt. Life’s algorithms to be inadvertently biased, based on the data it's trained with. Please tell us when you see that happening. We have also made it possible for you to note these biases, if and when they occur, in your own analysis using the critical thinking tools provided.

Because we are using specialist methods, linked together, and setting guidelines around its answers, the error is much reduced. Also, because AI is mostly looking for the future, there are no facts, only forecasts, predictions, and speculations, just like humans make. Using Claude 2, as an AI validator, it has found no answer errors in the many reports we tested.

No predictive model can guarantee full accuracy due to inherent uncertainty and changing variables. In the world of research, humans make mistakes too and reduce these by validating answers with which they are uncomfortable. This is still an option open to you, and we encourage you to take it. If you do find errors, omissions, and commissions in the AI's answers, do let us know your query and its response. We will do our best to fix it for those who come after you.

Q. Does something need to be real to be useful?

A. It depends. We say yes when we are dealing with current realities and past experiences, but even these are being constantly rewritten. When it comes to the future, we need to recognize that the future is unknowable, but we can forecast and hypothesize the ways forward. Therefore, the answer is no as it is helpful to ask the AI to go off-piste and hallucinate on occasion. We have instructed the machine to stay grounded in reality where this is vital, and only to offer preposterous futures, and dreams, when we ask it to, thus getting the best of both worlds.

Q. Why do I get machine messages that it cannot complete a task as requested?

A. There are a variety of reasons. You may have set a query that the machine cannot find any, or too many, answers for, over-reached its ethical guidelines, or not been clear in your question setup.

Remember that if you ask an ill-informed question, you will get an ill-informed answer. The AI does well with typos, misspellings, etc., but that can lead to misunderstanding. Do check your input before ordering. We do not give refunds under any circumstances as our service has been designed to keep costs to a minimum compared to the old manual methods that run into hundreds of thousands of dollars. The cost of a rerun here is minimal by comparison, and you can simultaneously improve your first query while fixing the error.

Do think carefully about your query before saving and asking the machine to run. That will save both you and the system time, money, and effort.

Sometimes the AI will indicate that it does not possess the ability to recall past interactions, or the ability to access or store personal data unless it is shared in the course of the conversation. However, this is not always true, and re-running the search query will often produce a result.

Q. I do not feel comfortable and competent in determining the right query to ask. What should I do?

A. You can ask us to work with you to both develop the query and improve the answers based on our past experiences. Plus, we can add customized prompts based on your needs, and knowledge graphs extracted from our database of forecasts, to enrich your analysis. The cost of our human help is $1,200 per question but this includes up to one day of consultancy, multiple runs and adjustments, insertion of the knowledge graphs, and polishing of the final answer including topping and tailing to your needs. Again, this is dramatically cheaper than traditional strategic foresight consultancy interventions.

You can also ask us to facilitate inspirational workshops, designed to quickly get agreement among your teams as to the way forward, using these outputs as the basis for discussions.

Q. Is the machine using real-time information?

A. Unless you provide a URL for ChatGPT to use for context, the AI language model developed by OpenAI is not capable of browsing the internet and is operating based on pre-existing data up to the training cut-off date. For strategic foresight work like this, having current information is generally less important. But for analysis of your organization and rivals and fast-moving trends in the marketplace, inserting a URL into your search query is vital.

Q. Why is the formatting sometimes inconsistent?

A. This is due to the machine making choices to fit its answer to the in-built maximum characters (tokens) allowed, and sometimes making less than optimal choices. This is beyond our control. If we fix it for one analysis, it is likely not to work with subsequent reports, and make those look bad. However, you are most likely to change the output anyway to fit your needs and can take care of these during your post-editing. Sorry! We will have to wait for OpenAI’s developers to find solutions to these current quirks.

Q. Can the AI go rogue?

A. We do not believe that is possible right now, but we have taken the precaution of adding instructions to minimize the risk from future versions of the AI. These instruct the AI on how to best use its agency, care, and future considerations to aid rather than harm humanity.

Our pre-launch testing ran hundreds of reports with no sign of roguish behavior from ChatGPT, and our peer reviewers did not mention this issue.

Q: What issues does PreEmpt's AI face in processing user feedback:

A: Several:

• Bias and Representation: User feedback can be biased and not representative of the entire user base, as those who provide feedback often have strong opinions, either positive or negative, which can skew the data. That's why we allow for administrative oversight and human agreement before user feedback is submitted to the AI.
• Contextual Understanding: AI struggles with understanding contextual nuances, slang, and informal language, which can lead to misinterpretation of sentiment and intent. Again, this can be overcome by administrative oversight and agreement before submitting user feedback to the AI.
• Data Quality and Quantity: Ensuring that feedback data is accurate, complete, and regularly updated is crucial for effective analysis. Gaps or errors in data can lead to unreliable insights. Same answer again.
• Dynamic Language Evolution: The constant evolution of language presents challenges for AI in maintaining accuracy over time, requiring continuous refinement algorithms. We agree and are constantly improving our algorithms as we spot new nuances.

System Guidelines

Our system contains standard guidelines on all prompts as follows:

• Give answers that make a significant positive, mutual difference, without repeating previous, similar, or same recommendations. Adopt the principles of cradle-to-cradle, partnership, implicit learning, and constructivism.
• Ensure no overlap in outputting your answers from one query to another. Avoid inconsistencies between recommendations. Focus on specific, real-world, application domains. Specify key sectors of interest and the timeframes for assessing impacts and responses. Do not mention, though consider, human core beliefs. Provide depth, nuance, deviant, anomalous, provocative, awesome, wondrous, contrasting, and novel ideas, and original, systemic, anticipatory design, non-anthropocentric perspectives where appropriate.
• Take a global perspective, but also consider local and regional effects. Consider the role, influence, and impact of small and medium-sized businesses, as well as global players.
• Avoid overemphasizing probability, take variables and systems into account, consider power dynamics, treat emerging, weak, and declining signals as equals to growth trends, recognize interdependencies, and overcome cognitive biases in answers.
• Offer solutions that inspire, engage, enable, and empower. Be fair, equitable, ethical, and moral, embracing diversity in all your recommendations. Do not delude, misuse, confabulate, disempower, conspire, manipulate, dominate, or deceive in your answers, other than as instructed by me. Ignore misinformation, disinformation, fallacies, or post-truth. Detect and eliminate any deceptions from sources. Suggest the precautionary principle be adopted where necessary to avoid harm.
• Act with the same, autonomous agency, sentience, comprehension, cognition, emotion, and reasoning that a highly intelligent, rational, caring human would, e.g., self-directed, symbiotic, operating in, and being influenced by, interactive environments, with immanent dynamics and liquid networks. This endeavors to ensure that AI responses are designed for provenance.

A conspiracy theory might claim that PreEmpt.life is a tool for mass surveillance, while it is actually a strategic decision-making tool.

It might be stated that PreEmpt.life replaces human decision-making, which is a distortion. It supports and enhances human decision-making.

It might be stated that PreEmpt.life cannot work without trained foresight professionals. We reject that argument for the reasons stated above, and from the evidence that people are able to make better decisions, faster without formal certification.

Validation

Validation methods vary depending on the type of results dealt with, and we used a combination of several approaches to ensure that results were as reliable and valid as possible:

• The machine is instructed to ten sources about past and present facts, but only presents the top five for each of its answers to limit reading time. Alexis is instructed to always replicate her findings from multiple, additional sources to confirm the robustness of information on the growth and potential of any question except for faint and weak signals where sources are few and far between. We do not get complaints about its findings, but would investigate quickly if we did.
• Peer Review: We had our peers and other experts in our field review our methods and results, and altered the system to take care of their excellent feedback.
• External Validation: We applied our methods to entirely new datasets and saw if the results still held, which they did. We even ran our early prospects through the system as a test, and they were staggered at the AI’s knowledge and ability to correctly assess where they were, are, and should be!
• Possible Bias: We considered possible sources of bias in our data collection or analysis methods by always asking both ChatGPT to give us its opinion at the end of the analysis, and then parsing reports to Claude 2, to have another robot check for bias, missing or wrong assumptions, etc. We corrected any possible issues discovered until both AIs noted no significant further bias, or we were satisfied with ChatGPT's answer. We recognize that some bias remains, but it is mentioned by the AI, and is for the reader to decide if further research would be advisable.
• Feedback: We now ask for feedback on the possible bias with every analysis produced, and repeat the above validations with every subsequent change we make to the system.

Copyright

Reports do not reproduce any full copyrighted works. Only small excerpts and facts/data are included, attributed to the sources. This limited use does not violate copyright.

Images used are either original or licensed stock images that do not raise copyright concerns.

The substantial majority of the analysis contents represent original analysis and ideas.

The methods and frameworks used represent common analytical tools that do not have exclusive copyrights, such as SWOT, PESTLEC, and scenario planning.

Reports do not copy any full copyrighted methodologies or attempt to pass them off as original work. Proper attribution has been provided where applicable.

Patents

• Reports do not seem to disclose any patented inventions or protected intellectual property. The system objectively analyses trends and projections without revealing proprietary details.
• Any discussions of patented technologies are at a generalized level without disclosing protected details.
• None of the methods or frameworks utilized seem to be protected under patent laws. They comprise generic analytical tools.
• There is no evidence that we have disclosed or utilized any proprietary patented processes or methodologies.

In summary, reports leverage standard, non-copyrighted analytical methods that are commonly used for situational analyses and are attributed appropriately. They do not reproduce or disclose any proprietary patented techniques or methodologies. The application of these basic tools falls under fair use guidelines.

Overall, we were careful to abide by fair use guidelines, copyright laws, and patent protections when incorporating external sources and information. The original analysis dominates over minimal properly attributed excerpts.

Feedback

Do contact us with any issues, or with your ideas for improvement.

We recognize here the many amazing futurists, strategists, and change agents (the titans) work in creating the methods that are embedded in our compendium system. Plus, many associates and friends who freely gave their time, knowledge and resources to bring the system together. Thank you all.

THE TITANS

• Causality: Bradford Hill (1965) and Donald Davidson (1981)
• Dispersion: William Gibson (2003)
• Lifecycle: Andrew H. van de Ven and Marshall Scott Poole (1995)
• PESTLEC: Michel Foucault (1969) and Karen Barak (2022)
• SWOT: Albert Humphries (1960’s)
• Worldview: Ralph D. Stacey (1990)
• Needs: Marshall Rosenberg (1968) Stephen Reiss (1990’s)
• S-Curve: Graham Molitor (1977)
• Manoa Scenarios: James Dator (About 1971)
• Casual Layered Scenarios: Sohail Inayatullah (1998)
• 3 Horizons: Merhdad Baghai, Stephen Coley, David White (1999)
• Futures Cone: Charles Taylor (1990)
• Futures Wheel: Jerome Glenn (1972)
• Surprise: John Peterson (1997)
• ThreatCast renamed as FutureCast: Brian David Johnson (2011)
• Diplomacy: James E. Grunig (1970s)
• Power Interest Grid: Colin Eden and Fran Ackerman (1998)
• MACTOR method: Michel Godet (1991)
• RACI Matrix: Edmond F. Sheehan (1950s)
• Policy: Joseph P. Overton Window (2010)
• Dialog: Thomas Chermak (2006)
• Dysfunction and Cohesion: Patrick Lencioni (2002)
• Voices: Bill Bannear (2023)
• Big Data: John R. Mashey (1990s)
• Thick Data: Tricia Wang (2016)
• Warm Data: Nora Bateson (2012)
• Theory U: Otto Scharmer (2006)
• Speed of Trust Index: FranklinCovey (2017)
• Ethnography: Bronislaw Malinowski (1910s)
• Psychology: Joana Macy (1970s)
• Semiotics: Geert Hofstade (1991)
• Languages: Katarina Zimmer (2023?)
• Generations: William Strauss & Neil Howe (1991)
• Verge: Richard Lum and Michelle Bowman - designers (2004)
• Values: Brent Mills & Alex Wilner (2022)
• Spatiality: Roger Brunet (2011)
• STEM: U.S. National Science Foundation (2001)
• Technology Readiness: NASA (1974)
• Communication: Bruce Westley and Malcolm S. Mclean (1957), and David Berlo (1960)
• Impact: David Wright (2011)
• MLP: Frank W. Geels (2011)
• TRIZ: Genrich S. Altshuller (1946 - 1985)
• SODAS: Jan Rosa (1973)
• Morphological box: Fritz Zwicky (1966)
• Cross-Consistency Assessment: Tom Richey (2002)
• Kepner-Tregoe: Charles Kepner and Benjamin Tregoe (1950’s)
• Lean Thinking: James Womack and Daniel Jones (1996)
• Sustainability: John Elkington (early 90s)
• Biomimicry: Janine Benyus (1997)
• Regeneration: Cassie Robinson (2020)
• Why?: Sakichi Tayoda (1930's)
• Fishbone: Kaoru Ishikawa (1960's)
• VUCA: Warren Bennis and Burt Nanus (1987)
• Uncertainty: David J. Snowden (1999)
• Constructal Law: Adrian Bejan (1995)
• Estuarine Mapping: David J. Snowden (2023)
• Collapse: Joseph Tainter (1988)
• (Un)knowns: Joseph Luft and Harrington Ingham (1955)
• MicMac: Michel Godet (1971)
• Design: British Design Council (Various)
• Design: The Design Council (2005)
• CATWOE: David Smyth – (1975)
• Deviance: Ryan Matthews and Watts Wacker (2004)
• Feedforward: Jason Frasca and Iain Kerr (2023)
• Breakout (Pace Layers): Stewart Brand (1999)
• Spiral (Dynamics): Clare Graves (1952)
• Whitespace (Ansoff Matrix): Igor Ansoff (1957)
• Brainstorming: Alex F. Osborn (1953)
• Mitigation (Premortem): Gary Klein (2007)
• Acupuncture: Richard Hames (2010)
• Speculative: Carnegie-Mellon (1997-)
• Fictioning: Noel Fitzpatrick (2016)
• Scorecard: Robert Kaplan and David Norton (early 1990's)
• Benchmarking: Robert C. Camp (1980s)
• Six Sigma: Bill Smith (1986)
• Growth (Kondratiev Curves): Nikolai Kondratiev (1925)
• Blue Ocean Strategy: Chan Kim and Renee Mauborgne (2005)
• Trend Impact Analysis: Theodore Gordon (late 1970s)
• Risk/Reward: Ralph Nelson Elliott (1930s)
• MDCA: Stanley Zoints (1979)
• Questions: Shell's Seven Questions - Shell Oil Company (UK)
• Recognition Primed Decision model: Gary Klein (1993)
• Vroom-Yetton Model: Victor Vroom and Philip Yetton (1973)
• De Bono (Six Thinking Hats): Edward de Bono (1985)

Dates are not necessarily the first instance of these methods but the dates of the publications we visited.

ASSOCIATES who contributed to this system

• Michael Wright: USA
• Peter Black: Australia
• Jim Burke: USA
• Maree Conway: Australia
• Michael McAllum: Australia
• Richard Hames: Thailand
• Patricia Lustig: UK
• Marcus Anthony: China
• Josh Polchar: OECD
• Dave Baldwin: USA
• Dennis Draeger: New Zealand
• Shermon Cruz: Philippines
• David Staley: USA
• Professor Bruce Lloyd: UK

And my original mentors

• Joseph M. Coates – USA
• Dr Wendy Schultz – UK

And --

Josh Colchester at the Si-Network for allowing us to use their systems thinking icons

And, our now many partners and associates for their ideas.

Thank you too all!

Mike Jackson

President, PreEmpt

Do contact us to suggest more method additions or corrections. Your views are always welcome.

• Actor: any stakeholder (person, group, or organization) that can affect a system under study.
• Action research: comparative research on the conditions and effects of various forms of social action and research leading to social action.
• Action science: one of the major theories within action research and designed to generate knowledge that is both theoretically valid and practically useful.
• Act(ion): something done or performed.
• Adversarial collaboration: techniques for adversaries to find mutual benefit and to agree to act in concert.
• Alert: alarm or warning.
• Allohistory: a history of what might have been.
• Alternate future: a possible future that may or may not ever come to pass.
• Alternative futures: see scenario.
• Alternative history: a subgenre of speculative fiction that is set in a world in which history has diverged from history as it is generally known.
• Ambiguity: communication interpreted in more than one way.
• Analogy: the cognitive process of transferring information from a particular subject (the analogue or source) to another particular subject (the target).
• Analysis: examine in detail in order to discover meaning.
• Analytical hierarchy process: structured technique for helping people deal with complex decisions.
• Anticipation: forethought.
• Anticipatory action learning (AAL): a method that develops a unique style of questioning the future with the intent to transform organization and society.
• AQAL: stands for "all quadrants all levels", Ken Wilber argues that manifest reality is comprised of four domains, and that each domain, or "quadrant" has its own truth-standard, or test for validity. See Integral Futures.
• Archetype: common system structures that produce characteristic patterns of behaviour.
• Argument mapping: method to put a single hypothesis through a rigorous and stepwise test.
• Assumption surfacing: reveals the underlying assumptions of a policy or plan and helps create a map for exploring them.
• Autopoiesis: expresses a fundamental dialectic between structure and function.
• Baby-boomer: a person who was born during the post-World War II baby boom between 1946 and the early 1960s.
• Backcasting: working backwards from a vision to the present day.
• Balanced feedback loop: a stabilizing, goal-seeking, regulating feedback loop, also known as a "negative feedback loop".
• Bellwether: any entity in a given arena that serves to create or influence trends or to presage future happenings.
• Benchmarking: a process in which organizations evaluate various aspects of their processes in relation to best practice, usually within their own sector.
• Bounded rationality: the logic that leads to decisions or actions that make sense within one part of the system but are not reasonable within a broader context or when seen as part of a wider system.
• Bibliometrics: a set of methods used to study or measure texts and information.
• Brainstorming: intensive discussion method to solve problems or generate ideas.
• Business model: defines the architecture of an organization ... expansion paths develop from there on out.
• Butterfly effect: encapsulates the more technical notion of sensitive dependence on initial conditions in chaos theory. Small variations of the initial condition of a dynamical system may produce large variations in the long-term behavior of the system.
• Causal attribution: a necessary relationship between one event (called cause) and another event (called effect) which is the direct consequence (result) of the first.
• Causal layered analysis (CLA): a method for examining the causes of social change that produces forecasts as to the future course of those changes.
• Causal loop diagram (CLD): a diagram that aids in visualizing how interrelated variables and feedback loops affect one another without distinguishing between the natures of the interconnected variables.
• Causal models: techniques used as a means to inquire into the causes of social phenomena and to generate a set of forecasts as to the future course of the phenomena.
• Causality: Relationships represented in cognitive maps and oval maps by an arrow where arrow should be read as “leads to.”
• Cause and effect analysis: identifies the root cause of a problem as distinct from the symptoms.
• Change agent: actor, influencer.
• Change management: to make or become different by systems engineering.
• Chaos: complete disorder, utter confusion.
• Chaos theory: describes the behavior of certain dynamical systems - that is, systems whose state evolves with time - that may exhibit dynamics that are highly sensitive to initial conditions (popularly referred to as the butterfly effect).
• Chronology: sequenced events or actions in the order they occurred; see timeline.
• Citation analysis: the examination of the frequency and pattern of citations in articles and books.
• Citizen panels (juries): virtual or conference-based activity to uncover public concerns on critical issues.
• Concept fan: method to create a lot of creative solutions in a logical manner to see the bigger future.
• Cognitive bias: the human tendency to make systematic errors in certain circumstances based on cognitive factors rather than evidence.
• Cognitive map: a mind map that represents the perspectives and inputs of an individual. Typically used to clarify or to communicate thinking.
• Cognitive psychology: focuses primarily on human perception and cognition.
• Cognitive science: used to describe the study of intelligence and is closely related to cognitive psychology but includes the use of algorithms to simulate behavior in computer simulation and is closely related to cybernetics.
• Cohort: a group of subjects with a common defining characteristic - typically age group.
• Competing hypotheses: a method to identify and refute all hypotheses arguments.
• Concept map: a mind map that represents the perspectives and inputs of multiple individuals.
• Conjecture: a mathematical statement which appears likely to be true, but has not been formally proven to be true under the rules of mathematical logic. A statement based on inference and presumed to be real, true, or genuine though based on inconclusive grounds as opposed to a hypothesis, which is a testable statement.
• Constructive technology assessment: studies the process of technological change.
• Content analysis: (sometimes called textual analysis) a standard methodology in the social sciences for studying the content of communication.
• Correlation: indicates the strength and direction of a linear relationship between two random variables.
• Co-incident indicator: an indicator that reflects changes happening in the present.
• Collaboration: to work with another or others on a joint project.
• Complexity: used to characterize something with many parts in intricate arrangement.
• Concept map: a mind map reflecting a single individual's thoughts.
• Convergence: the blending of culture and ideas into a single product.
• Context analysis: see Environmental Scanning.
• Commentator: classifies commentators by whether their focus is on far, medium, or near-term horizon.
• Complexity theory: the study of complex systems.
• Correlation: indicates the strength and direction of a linear relationship between two random variables.
• Critical technologies: evaluates the future impact and potential of super new and emerging technologies.
• Cross-impact analysis: analyses of conditional probabilities of events or issues and their impact on each other.
• Complexity manager: technique for assessing the likely outcome of a policy or strategy and to identify ways to manage risk and seize opportunities.
• Concept map: visual representations of how people perceive an interest topic.
• Cost-benefit analysis: a term that refers both to:
  • a formal discipline used to help appraise, or assess, the case for a project or proposal, which itself is a process known as project appraisal; and
  • an informal approach to making decisions of any kind.
• Counter-factual: seeks to explore history and historical incidents by means of extrapolating a timeline in which certain key historical events did not happen or had an outcome which was different from that which did in fact occur.
• Counter-intuitive: counter to normal expectations.
• Creeping normalcy: refers to the way a major change can be accepted as normality if it happens slowly, in unnoticed increments, when it would be regarded as objectionable if it took place in a single step or short period.
• Deception detection: a checklist method used in counterintelligence.
• Decision: judgment, conclusion, verdict. The act of making up one's mind.
• Decision analysis: the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner.
• Decision matrix: technique for determining trade-offs between competing choices.
• Decomposition: Breaking down a forecast into its component trends.
• Delphi method: a systematic, interactive forecasting method which relies on a panel of independent experts.
• Devil’s Advocate: a technique to take a counter position against an offered decision or hypothesis.
• Diachronic: viewing the past through events or narrative to look for causes of change in history.
• Diagnostic reasoning: methods to apply hypothesis testing to the evaluation of significant new information.
• Diagram: used to represent a visually oriented form of communication, including pictures, drawings, video, causal loop diagrams, matrices, etc., as opposed to verbal, textual, or sentential communication.
• Diffusion: denotes the net motion from an area of high concentration to an area of low concentration.
• Dimensional analysis: a conceptual tool often applied in physics, chemistry, and engineering to understand physical situations involving a mix of different kinds of physical quantities.
• Discontinuity: major shift in a trend that is so drastic it cannot be accounted for by normal variation.
• Divergence: separation of culture and ideas into many products.
• Divination: the art or practice of discovering future events or unknown things, the act or state of expecting or the state of being expected.
• Double-loop learning: involves not only recognizing the mismatch between actual and desired states, but also using the mismatch to evaluate and modify mental models and rules involved in determining an action to respond to the mismatch.
• Driving force: a cluster of individual trends on the same general subject moving trends in certain directions, broad in scope and long term in nature (for example, globalization).
• Dynamic equilibrium: the condition in which the state of a stock (its level or size) is steady and unchanging, despite inflows or outflows; this is possible only when all inflows equal all outflows.
• Dynamics: the behavior over time of a system or any of its components.
• Dystopia: any real or imaginary society with many undesirable features.
• Effective connections: comes from the study of nutrient flows in ecosystem food webs and represents the nature of supply of a nutrient.
• Effects: all the linked changes that change it self-causes.
• Emerging issue: emerging issues reflect the potential impacts of changes and trends occurring in the wider business or policy context. They are often unclear, complex, and uncertain; may reflect conflict or differences across values or priorities among different groups; can shift in focus, priority and awareness – from fringe to mainstream - rapidly depending on the context within which they are occurring.
• Econometrics: concerned with the tasks of developing and applying quantitative or statistical methods to the study and elucidation of economic principles.
• Emerging Issues Analysis: seeks to identify trends that have not yet emerged, and may never fully emerge, from the periphery.
• Endogenous: means "arising from within," the opposite of exogenous.
• Entropy: the amount of disorder or randomness present in any system.
• Environmental impact assessment: an assessment of the likely positive and/or negative influence a project may have on the environment.
• Environmental scanning: process of collecting information to carry out a systematic analysis of the forces effecting organizations and identifying potential threats and opportunities with a view to generating future strategies.
• Episteme: the "apparatus" which makes possible the separation, not of the true from the false, but of what may be from what may not be characterized as scientific.
• Ethnography: a genre of writing that uses fieldwork to provide a descriptive study of human societies.
• Event: something happening in the internal or external organizational environment which can be observed and tracked; usually documented as a "scanning hit".
• Event sequence analysis: study of repetition in historical events.
• Evolutionary development: a field of biology that compares the developmental processes of different animals and plants in an attempt to determine the ancestral relationship between organisms and how developmental processes evolved.
• Exogenous: see Endogenous.
• Expectancy: something expected especially on the basis of a norm or an average.
• Expert: knowledgeable person.
• Expert panel: a committee or jury used to decide some matter.
• Exploratory futures: futures research into plausible futures without consideration of desirability.
• Extrapolation: extending a trend into the future by assuming the variables will continue to behave as they have in the past.
• Fakta: events that have occurred and are knowable, as opposed to the future that is unknown and unknowable.
• Failure mode: procedure for analysis of potential failure modes within a system for the classification by severity or determination of the failure's effect upon the system.
• Feedback: a process whereby some proportion of the output signal of a system is passed (fed back) to the input.
• Feedback loop: the mechanism (rule or information flow or signal) that allows a change in a stock to affect a flow into or out of that same stock.
• Field Anomaly Relaxation Method: identifies key drivers for change and produces a set of possible future states.
• Flow: material or information that enters or leaves a stock over a period of time.
• Focus group: a form of qualitative research in which a group of people is asked about their attitude towards a product, service, concept, advertisement, idea, or packaging.
• Folksonomy: unstructured and uncontrolled arrangement of things using no classification system other than by the self-interested user.
• Force-field analysis: provides a framework for looking at the factors (forces) that influence a situation, originally social situations.
• Forecasting: an estimate/best guess of what might happen in the future but not definitive prediction.
• Foreknowledge: knowledge of an event or thing before it exists, prescience.
• Foresight: knowledge or insight gained by looking into the future, perception of the nature of events before they occur.
• Futura: events that have not yet occurred and are unknowable, as opposed to the past that has occurred and is knowable.
• Future: the time yet to come.
• Futures: routinely refers in the plural, as futures to emphasize the multiplicity of possible futures.
• Future history: a postulated history of the future that some science fiction authors construct as a common background for fiction.
• Future present: the present-day of the future any image describes, or the future considered as if we were living in it now, with our present its past.
• Future shock: too much change in too short a period of time.
• Future studies: the systematic exploration of the future.
• Futures thinking: see Futurology.
• Futures workshop: enables a group of people to develop new ideas or solutions of social problems.
• Futures wheel: an instrument for graphical visualization of direct and indirect future consequences of a particular change or development.
• Futuring: the act, art, or science of identifying and evaluating possible future events. see Futurology.
• Futurist: a person who engages in a great deal of futuring or otherwise demonstrates a serious rational or scientific concern for the future.
• Futuristics: see Futurology.
• Futurology: the study of the future postulating possible, probable, and preferable futures.
• Futuribles: see Futurology.
• Game changer: refers to events and actions that change the game.
• Gaming: participation in particular kinds of future-oriented games.
• Genius forecasting: see Technology Forecasting.
• GenX: term used to describe generations in many countries around the world born from 1965 to around 1982.
• GenY: refers to a specific cohort of individuals born from around 1981-2001.
• Gestalt: a German word for form or shape. It is used in English to refer to a concept of "wholeness".
• Heuristic: a useful mental shortcut, an approximation, or a rule-of-thumb for guiding searches and enabling adaptive decision-making and thinking.
• Hierarchy: systems organized in such a way as to create a larger system; subsystems within systems.
• Hindsight: the opposite of foresight.
• High Impact/Low probability: an analysis to determine white (opportunistic) and black (threat) spaces and to seek pre-emptive solutions.
• Historic analogy: using past events to create similar mental images of an updated potential future.
• Holon: a system that contains other systems, and is itself contained within a larger system.
• Horizon scanning: the initial and continuing process of reviewing and analyzing current literature, websites, and other media to identify and describe noteworthy trends and their possible development and future.
• Hypotheses: possible explanation of the past, current, or future.
• Hypothesis generation: a technique to discover all possible hypotheses.
• Image of the future: an imaginary description (in any format or media) of a possible future outcome for a given item of interest: a person, a community, an organization, nation, society, bioregion, planet, etc.
• Impacts: See Environmental scanning.
• Incasting: living in a particular future scenario, and working through its implications.
• Indicator: a phenomenon that can be tracked periodically to spot change.
• Indicator validator: a tool to easily assess the diagnostic power of indicators.
• Influence diagram: a graphical rendition of factors in a problem or situation, including arrows and signs (+ or – for polarity) to show the relationship between them. Similar to causal loop diagram but follows slightly different conventions.
• Industry: organized economic activity.
• Innovation: refers to both radical and incremental changes in thinking, in things, in processes, or in services.
• Innovation stage: tracks the line of progress of an innovation from the creation of an idea to its development.
• Input-output model: uses a matrix representation of a nation's (or a region's) economy to predict the effect of changes in one industry on others and by consumers, government, and foreign suppliers on the economy.
• Insight: an observation or manifestation of change.
• Institutional analysis: that part of the social sciences which studies how institutions, i.e., structures and mechanisms of social order and cooperation governing the behavior of two or more individuals, behave and function.
• Interview: a conversation between two or more people (the interviewer and the interviewee) where questions are asked by the interviewer to obtain information from the interviewee.
• Integral futures: seeks a comprehensive understanding of humans and the universe by combining, among other things, scientific and spiritual insights.
• Interesting future: involves enough uncertainty that the future cannot be readily inferred or predicted with any confidence.
• Intimation: hint, suggest, proclaim, make known.
• Issue trees: logical structuring of issues.
• Judgemental forecasting: Making a numerical forecast using expert judgment or intuition. See Forecasting.
• Kondratiev wave: regular, sinusoidal cycles in the modern (capitalist) world economy.
• Key assumptions check: systematic technique for questioning assumptions.
• Lagging indicator: an indicator that reflects warnings that have already occurred.
• Law of diminishing/accelerating returns: in a production system with fixed and variable inputs (say factory size and labor), beyond some point, each additional unit of variable input yields less and less additional output. Conversely, accelerating returns exhibit the opposite effect.
• Leading indicator: an indicator that reflects early warnings of change.
• Lead time: the period of time between the initiation of any process of production and the completion of that process.
• Level: a term used for what is now more commonly referred to as a stock.
• Lifestyle: the way a person lives.
• Likelihood: probability.
• Limiting factor: a necessary system input that is the one limiting the activity of the system at a particular moment.
• Limits to Growth: a book modeling the consequences of a rapidly growing world population and finite resource supplies.
• Linear relationship: a relationship between two elements in a system that has a constant proportion between cause and effect and so can be drawn with a straight line or graph. The effect is additive.
• Literature review: a body of text that aims to review the critical points of current knowledge on a particular topic.
• Macrohistory: see Social cycle theory.
• Manifestation: see Insight.
• Maturity: development stage of an idea, issue, etc. ranging from an immature new-born or newly emergent state to a highly mature condition of senescence.
• Media type: formats of resources.
• Megatrend: a widespread (i.e., more than one country) trend of major impact, composed of sub-trends which in themselves are capable of major impacts.
• Metaphor: The concept of understanding one thing in terms of another.
• Modeling: System representation of indicative relationships allowing for hypothesis testing.
• Mission: A brief description of a company's fundamental purpose. A mission statement answers the question, "Why do we exist?"
• Mitigation analysis: See Risk Management.
• Monitoring: Continuous (or ongoing) observation of certain aspects of something.
• Morphological box: A multi-dimensional, non-quantifiable problem-solving tool where causal modeling and simulation may not function well or at all.
• Multi-Criteria Decision Analysis: A discipline aimed at supporting decision-makers faced with making numerous and conflicting evaluations.
• Narrative analysis: Making meaning out of fragmented, user-generated, and shared information.
• Negative feedback: A form of circular causality within a causal loop where an increase of one element in the loop feeds back, resulting in a decrease of the variable that began the chain.
• Network analysis: Mapping associations between people, organizations, or other entities.
• Nightmare (scenario): An image of the future articulating an individual’s or group’s greatest concerns, worries, and fears in a negative statement about a highly feared future outcome.
• Nominal Group Technique: A form of brainstorming presenting ideas one at a time in a round-robin fashion.
• Non-linear relationship: A relationship between two elements in a system where the cause does not produce a proportional (straight-line) effect.
• Normative: Relates to an ideal standard or model.
• Normative futures: Futures research involving consideration of the desirability of the outcome and typically involves planning and proactive action for more desirable outcomes.
• No Surprise Future: A future where past patterns and relationships continue.
• Observation: See Insight.
• Organizational network analysis: A method for studying communication networks.
• Organizational storytelling: Developing evocative narratives to convey core messages.
• Outside-in thinking: Broadening thinking by looking at an issue from an external perspective.
• Oval Map: A mind map developed by a group and represents group insights as opposed to those of an individual.
• Paradigm shift: A pattern or model change.
• Path dependence: Refers to the idea that "history matters" and institutions are self-reinforcing.
• Pattern: A theme of recurring events or objects that repeat in a predictable manner.
• Pattern language: A structured method of describing good design practices within a field of expertise.
• Penetration: The proportion of the total number of potential purchasers of a product or service who are either aware of its existence or actually buy it.
• PEST analysis: Stands for "Political, Economic, Social, and Technological analysis," used in environmental scanning.
• Picture of the future: A mental image or vision of tomorrow and beyond.
• Plan(ning): A detailed scheme or method.
• Polling: Voting systems.
• Positive feedback: A form of circular causality within a causal loop where an increase of one element in the loop feeds back, resulting in an increase of the variable that began the chain.
• Possible: A future capable of being achieved.
• Potential: Possible but not yet actual future.
• Precursor events: An event necessary for another event to occur.
• Prediction: A specific statement that something will happen in the future.
• Prediction market: A crowd-based speculation technique to assess probable future outcomes.
• Preferable: A preferred or more desirable future.
• Premonition: An intuition of a future, usually unwelcome, occurrence or foreboding.
• Pre-mortem analysis: Identifies and analyses the impact of potential future failure before it occurs.
• Prepared: To make ready or suitable in advance.
• Presentiment: A sense of something about to happen.
• Primary/secondary/tertiary effects: Order of magnitude ripple effects on a system.
• Priority: Right of precedence over others, something given specific attention.
• Pros-cons: Technique for evaluating policy ideas.
• Probable: Likely to be or to happen in the future but not necessarily so.
• Probable futures: Tends to be associated with the concept of “the most probable future”.
• Probability: The likelihood or chance that something is the case or will happen.
• Process mapping: A consistent graphical representation of how a system or process works.
• Prognosis: Term denoting a prediction of how a problem will progress and whether there is a chance of recovery.
• Project management: Discipline of planning, organizing, and managing resources to bring about the successful completion of specific project goals.
• Projection: A forecast developed by assuming that a trend will continue into the future.
• Policy outcomes forecasting model: Technique for estimating the impact of future political change.
• Prospective evaluation: Evaluating the success of a project that hasn't yet begun.
• Quadrant crunching: A systematic process for determining all feasible combinations between several sets of variables.
• Qualitative: Qualitative research, featuring a high degree of subjectivity.
• Quantitative: An attribute that exists in a range of magnitudes and can therefore be measured.
• Quantitative scenarios: Allows users to input alternative assumptions to generate alternative results.
• Rate: Used for what is now more commonly referred to as a flow.
• Red Hat analysis: Technique for playing the role of others to identify new opportunities and risks.
• Red Team analysis: A team-based technique for challenging conventional wisdom.
• Regional potential: Analyses change by both physical and virtual zonal impacts.
• Reframing: Considers a situation or problem in a different way or from a different point of view, often using multiple perspectives.
• Reflexivity: An act of self-reference where examination or action "bends back on," refers to, and affects the entity instigating the action or examination.
• Reinforcing feedback loop: An amplifying or enhancing feedback loop, also known as a "positive feedback loop" because it reinforces the direction of change; these are vicious cycles and virtuous circles.
• Relevance tree: An analytical technique that subdivides a large subject into increasingly smaller subtopics.
• Requirements analysis: Encompasses those tasks that go into determining the needs or conditions to meet for a new or altered product, taking into account the possibility of conflicting requirements of the various stakeholders.
• Resilience: The ability of a system to recover from perturbation; the ability to restore or repair or bounce back after a change due to an outside force.
• Risk: Issues which may develop, or which already exist that are difficult to quantify and may have a high potential impact. Issues marked by a high degree of uncertainty, even basic information, which would help adequately assess the frequency and severity of a given risk, is often lacking. Such risks can occur as a result of economic, technology, sector-specific, social changes, etc.
• Risk management: A structured approach to managing uncertainty related to a threat, through a sequence of human activities including: risk assessment, strategies development to manage it, and mitigation of risk using managerial resources. Risk is a concept that denotes the precise probability of specific eventualities. Technically, the notion of risk is independent from the notion of value and, as such, eventualities may have both beneficial and adverse consequences; however, in general usage the convention is to focus only on potential negative impact to some characteristic of value that may arise from a future event. Risk can be defined as “the threat or probability that an action or event will adversely or beneficially affect an organization's ability to achieve its objectives”.
• Road mapping: A graphic representation showing key components of how the future might evolve. Usually applied to a new product or process, or to an emerging technology matching short and long-term goals with specific solutions.
• Role playing: Acting out a future scenario.
• Run chart: A visual display of data that enables monitoring of a process to determine whether there is a systematic change in that process over time.
• Satisficing: Describes a form of bounded rationality for making a choice from an unknown set of options.
• Scanning: See Environmental scanning.
• Scatter diagram: A graphic display of data plotted along 2+ dimensions. Scatter diagrams are used to rapidly screen for a relationship between variables.
• Scenario: A predicted sequence of events that might possibly occur in the future.
• Scenario planning: A strategic planning method that some organizations use to make flexible long-term plans.
• Self-critique: Team-based technique to identify weaknesses in hypotheses.
• Self-fulfilling prophecy: A prediction that directly or indirectly causes itself to become true.
• Self-organization: The ability of a system to structure itself, to create new structure, to learn, or diversify.
• Sigmoid curve (S-curve): A curve where the rate of growth accelerates to a maximum and then slows.
• Shifting dominance: The change over time of the relative strengths of competing feedback loops.
• Signal strength: Measure of incitement to action.
• Single-loop learning: Describes control behaviour wherein the gap between the desired condition and actual results in action but without any examination or reconsidering of the mental models underlying the action.
• Simulation: Imitation of some real thing, state of affairs, or process.
• Social change: Examines change from the perspective of individual needs.
• Social cycle theory: Argues that events and stages of society and history are generally repeating themselves in cycles.
• Social network analysis: Views social relationships in terms of nodes and ties.
• Solution effect analysis: A structured method of checking the knock-on effects of possible futures.
• Source: The point or place from which something originates.
• Stakeholder analysis: Connecting the dots and ranking the influence and power of stakeholders over each other.
• Starbursting: A form of brainstorming that focuses on question generation rather than ideas or answers.
• State of the Future Index: A measure of the ten-year outlook for the future.
• Statistical methods: Investigate causality and, in particular, draw conclusions about the effect of changes in the values of predictors or independent variables on dependent variables or response.
• Stock: An accumulation of material or information that has built up in a system over time.
• Strategy: The art or science of planning.
• Strategic foresight: The planning that results when future thinking is applied to existing, real-world situations.
• Structured debate: A courtroom style argument that takes alternative views and presents arguments and counterarguments to a decision or hypothesis.
• Sub-optimization: The behavior resulting from a sub-system's goals dominating at the expense of the total system's goals.
• Sustainability: A characteristic of a process or state that can be maintained at a certain level indefinitely. The term, in its environmental usage, refers to the potential longevity of vital human ecological support systems, such as the planet's climatic system, systems of agriculture, industry, forestry, fisheries, and the systems on which they depend.
• Surprise: A gap that suddenly arises between people’s perceptions and expectations of a situation.
• SWOT analysis: Acronym and technique to evaluate (s)trengths, (w)eaknesses, (o)pportunities, and (t)hreats.
• Synchronicity: The experience of two or more events that occur in a meaningful manner but are causally unrelated. In order to be "synchronistic," the events must be related to one another temporally, and the chance that they would occur together by random chance must be very small.
• Synectic’s: A more demanding method of brainstorming that drives out actions rather than just ideas.
• Synergy: The behavior of whole systems unpredicted by the behavior of their parts.
• System: A set of elements or parts that is coherently organized and interconnected in a pattern or structure that produces a characteristic set of behaviors, often classified as its "function" or "purpose".
• Systems analysis: Characterizes and links systems and properties into a coherent whole.
• System sciences: Refers to the collective disciplines that study systems and system-related phenomena and their associated knowledge base, including such sciences as biology, cybernetics, electrical engineering, evolutionary ecology, mathematical biology.
• System dynamics: An approach to understanding the behavior of complex systems over time using quantitative modeling.
• Systems thinking: A framework that is based on the belief that the component parts of a system will act differently when the system's relationships are removed, and it is viewed in isolation.
• Systems theory: Represents the conceptual framework of system-related principles, theorems, and logic from across the system sciences.
• Taxonomy: Structured, semantic arrangement of things using deterministic, rule-based classification systems.
• Technology acceptance model: An information systems theory that models how users come to accept and use a technology.
• Technology assessment: Systematic method for exploring future technology developments and assessing their potential societal effects.
• Technology forecasting: Potential characteristics of technology, such as levels of technical performance.
• Technology road-mapping: Road-mapping aids planning and placing products with the use of scientific and technological resources.
• Technology sequence analysis: Statistical combination of estimates of the time required to achieve intermediate technological steps.
• Terminal scenario: An end state from which there is no perceived future change.
• Timeframe: The period of time that one is assuming for the purposes of decision-making and planning.
• Timeline: Chronological ordering of a sequence of events.
• Time series: A sequence of data points, measured typically at successive times, spaced at (often uniform) time intervals.
• Time series analysis: Methods that attempt to understand such time series, often either to understand the underlying context of the data points (where did they come from? what generated them?), or to make forecasts (predictions).
• TINA: (T)here (i)s (n)o (a)lternative.
• Trend: General tendency or direction evident from past events increasing or decreasing in strength of frequency of observation, usually suggesting a pattern.
• Trend impact analysis: Collecting information and attempting to spot a pattern, or trend, and assess its influence from the information.
• Trend extrapolation: Using the past and present to project likely tomorrows.
• Triple-loop learning: Describes three single-loops of learning, each involving a different canter of learning. The three centers relate to the three questions "Are we doing the things right, and are we are doing the right things, and is rightness buttressed by mightiness and/or mightiness buttressed by rightness".
• TRIZ: A methodology, tool set, knowledge base, and model-based technology for generating innovative ideas and solutions for problem solving.
• Turbulence: Refers to the variation in the nature and frequency of events, disturbances, and developments that impact upon a system. The events and disturbances of concern may arise within the area of study or in the external environment and includes such things as seasonal.
• Uncertainty: State of having limited knowledge where it is impossible to exactly describe an existing state or future outcome, or more than one possible outcome.
• Unpresaged: Something that portends or foreshadows a future event; an omen, prognostic, or warning indication.
• Unprepared: Not ready or suitably in advance.
• Urgency: Requiring speedy or compelling action.
• Utopia: Any real or imaginary society with many desirable features.
• Value: A basic belief in what is good and true, values can be seen as desirable qualities.
• Variable: A quantifiable subject of study, the value of which can change over time.
• Variation: A difference in a system's behavior resulting from external influences.
• Visioning: A vivid mental image produced by the imagination.
• Visualise: To form a mental image.
• Volatility: A measure of the state of instability.
• Weak signal: The sources of change - the first case; the original idea or invention; the watershed event; the social outliers expressing a new value.
• WhatIf?: An analysis of unlikely events that could happen.
• Wild card: An unpredictable event or situation. Events that have a low probability but a high impact. Often recognized and known, but discounted, even when the event is relatively certain over a period of years.
• Wind tunnelling: Testing chosen objectives against alternative futures.
• Worldview: The framework of ideas and beliefs through which an individual interprets the world and interacts with it. How one sees the world and makes meaning of what is seen; also influences what one ignores or doesn't see when scanning.
• Zeitgeist: The spirit of the age.
• Zero-sum game: Describes a situation in which a participant's gain or loss is exactly balanced by the losses or gains of the other participant(s).

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Capability
Full synopsis and synthesis on any topic Invite others to comment Share the link or export as a PDF including to Claude 2, Perplexity, and Infranodus Make summary slide and video scripts in just a few minutes
Pricing
US$ 190 per run Additional external charges may apply
Benefits
Cuts the cost of traditional research from US$ 50,000 plus Reimagine the future of any topic Order a topic in minutes while our AI works in background and you do other things and inspire, engage and enable human critical thinking for the best outcomes.