Deception by DesignDeception by Design

Occasional essays on the art, science and psychology of deception and counterdeception.

Simon Henderson is an independent deception consultant working in the UK and the US.  His career has involved researching, teaching, and consulting on deception, counter-deception, information operations and cyber operations within a variety of government, military, and law enforcement organisations.  He is a keen student of magic and is passionate about novel and pro-social applications of deception.

One Thousand Words for Snow: Language, Perception, and Deception

By Simon Henderson on

In the introduction to his 1911 book, Handbook of American Indian Languages (Boas, 1911), anthropologist Franz Boas instigated the claim that Inuits have tens, if not hundreds, of words for snow. The popular press reported the claim widely, catching the public’s imagination. However, many linguists viewed the claim as an urban legend, the result of sloppy scholarship and journalistic exaggeration (Robson, 2013).

Later research not only validated Boas but found that other languages, such as the Sámi languages of Norway, Sweden, and Finland, have at least 1000 words (more accurately, lexemes, or lexical units of meaning) for snow (Jernsletten, 1994; Magga, 2006; Krupnik & Müller-Wille, 2010).

Sámi languages include (among other categories) words for:

  • The condition and layering of snow (balled, crusted, brittle, etc.).
  • How snow affects movement (heavy going, very slippery, drifting, drifted, etc.).
  • How snow interacts with water (ice on saltwater, rough sheet over water, non-weight-bearing over water, etc.).
  • And how snow settles upon and coats other objects (coated in frozen sleet, rounded sheet, melting rime, etc.).

As Sámi languages have at least 1000 words for snow, it follows that its speakers can notice, perceive, and discriminate between 1000 different types of snow in their environment. A relationship, therefore, exists between language, attention, perception, and sensemaking.

Theories and studies of linguistic relativity contend that spoken language influences thought and that linguistic categories limit and determine cognitive categories (Ahearn, 2021, p.69). Linguistic categories thus influence directly perceptual discrimination — our ability to notice and differentiate between features in our environment. This concept is central to the ‘Sapir–Whorf hypothesis’ (Whorf, 1956; see also commentary by Werner, 1994, 3656-3662), and it has important implications for the study and practice of deception.

Imagine that you are required to deceive a target from the UK to believe that it has snowed overnight outside their house. A strange mission, I acknowledge, but how might you seek to achieve this goal?

One approach might be to rent a commercial snow machine, attach it to a long hose, place the device in a soundproof box, and, under cover of darkness, use it to create an extensive snow scene outside the target’s house.

Now imagine that the target is not from the UK but a Sámi language area. Knowing that the target can perceive and differentiate between 1000 different types of snow, you may now be concerned that the commercial snow machine will simply not (if you will forgive the pun) cut the ice. It is unlikely that the machine will generate or distribute snow in a way that appears natural and will fool the target. The example is abstract and illustrative, but the principle applies directly to more serious applications.

Understanding the link between language and sensemaking is important when deceiving a target from a different culture. Deception relies upon inducing a target to make erroneous sense of a situation by presenting them with false but recognisable patterns. And while the deceptive patterns found across cultures are highly similar (and therefore transferable), the cues that constitute the patterns are often culturally specific and may differ widely.

The study, conduct, and countering of deception necessitates a raft of other cultural considerations (and, notably, many human vulnerabilities to deception transcend culture). Nonetheless, the language spoken by the target is a significant factor that can be easy to overlook, especially when deception is based upon object manipulation.

Note also that understanding a target’s language may reveal additional exploitable opportunities, as alluded to by Wittgenstein:

“The limits of my language mean the limits of my world.”

Wittgenstein (1921/2010, p.74).

References

Ahearn, L. M. (2021). Living language: An introduction to linguistic anthropology. John Wiley & Sons.

Boas, F. (1911). Introduction. Handbook of American Indian Languages (Vol. 1). US Government Printing Office (Smithsonian Institution, Bureau of American Ethnology). 

Jernsletten, N. (1994). Tradisjonel samisk fagterminologi. I: Dikka Storm, Nils Jernsletten, Bjørn Aarseth og Per Kyrre Reymert (red.) Festskrift til Ørnulv Vorren. Tromsø Museums Skrifter XXV. Tromsø Museum Universitetet i Tromsø, 234-253.

Krupnik, I. & Müller-Wille, L. (2010). Franz Boas and Inuktitut terminology for ice and snow: From the emergence of the field to the “Great Eskimo Vocabulary Hoax”. SIKU: Knowing our ice. Springer, pp. 377-400.

Magga, O. H. (2006). Diversity in Saami terminology for reindeer, snow, and ice. International Social Science Journal, 58(187), 25-34.

Robson, D. (2013). There really are 50 Eskimo words for ‘snow’. Retrieved 28/03/2022 from https://www.washingtonpost.com/national/health-science/there-really-are-50-eskimo-words-for-snow/2013/01/14/e0e3f4e0-59a0-11e2-beee-6e38f5215402story.html.

Werner, O. (1994). Sapir-Whorf Hypothesis. In K. Brown (Ed.), The Encyclopedia of Language and Linguistics (Vol. 7, pp. 3656-3662). Paragon Press and Aberdeen University Press.

Whorf, B. (1956). Language, Thought, and Reality: Selected Writings of Benjamin Lee Whorf. In J. B. Carroll (Ed.). MIT Press.

Wittgenstein, L. (1921/2010). Tractatus logico-philosophicus. London: Kegan Paul, Trench, Trubner & Co., Ltd.

Beyond Sun Tzu: A Database of Deception Quotations

By Simon Henderson on

“… (I forget where I read this, but if my memory serves me it was in some reliable source).”

Russell (1958, p.47)

“I love quotations because it is a joy to find thoughts one might have, beautifully expressed with much authority by someone recognized wiser than oneself.”

Dietrich (1962/2012, p.125)

“All warfare is based on deception. Hence, when we are able to attack, we must seem unable; when using our forces, we must appear inactive; when we are near, we must make the enemy believe we are far away; when far away, we must make him believe we are near.”

Tzu, S. (c500 BCE, Chapter 5)

Sun Tzu’s quotation is ubiquitous throughout the field of deception. It features in most articles, papers, and presentations that address the topic.

However, the quotation is a gross mistranslation. And it is plainly false. All warfare is not based on deception and the passage’s ‘musts’ are not always advantageous or advisable. For a summary comparison of eight popular translations of the multiple and fragmentary ‘original’ Chinese versions of ‘The Art of War’ (note that even this title is inaccurate), see Gagliardi (n.d.). And for an excellent discussion of myriad problems arising from mistranslations and misinterpretations of the work, see Whaley (2013). 

Why is this clichéd, mistranslated, and misleading passage from Sun Tzu so pervasive and persistent? From personal experience, I would suggest it is because insightful, illuminating, and authoritatively sourced quotations about deception are extremely thin on the ground.

I have been collecting and cataloguing quotations on deception for over 15 years. My quotation database has been one of the secret weapons I rely on whenever I write anything about the topic. However, tracking down a published source for any quotation, never mind some obscure quotation about deception, frequently entails tortuous, time-consuming detective work. And after hours of fruitless searching, having to jettison the perfect quotation, bon mot, or apophthegm, can be extremely frustrating.

Given the colossal number of hours I have spent populating my database, I have become rather protective of it. However, I have now decided to share it, in the hope that this might help or inspire others looking for the perfect pithy quotation about deception.

The database contains complete references for every quotation I have published. However, due to limitations in time and (quite frankly) inclination, many other quotations remain only partially sourced. For example, many identify only the individual to whom the quotation is commonly attributed. And the database also includes a variety of proverbs of highly dubious provenance.

Feel free to use the database at your own risk! And please let me know of any more complete sources, suggested corrections, duplicate entries, or new references that could extend its scope.

The database is available here.

References

Dietrich, M. (2012). Marlene Dietrich’s ABC: Wit, Wisdom. Open Road Media: New York. Originally published in 1962, by Doubleday.

Gagliardi, G. (n.d.). Comparing English Translations [of Sun Tzu’s work]. Retrieved 24/01/2022 from https://scienceofstrategy.org/main/content/comparing-english-translations

Russell, B. (1958). The Will to Doubt. New York: The Philosophical Library.

Tzu, S. (c500 BCE). The Art of War, Chapter 5.

Whaley, B. (2012). Sun Tzu: The Principles Of War. Somerville, Massachusetts: Lybrary.com.

The Library of Mistakes

By Simon Henderson on

There is a library in Edinburgh, Scotland, called The Library of Mistakes. It aims to improve understanding about how and why economic models fail.

“In recent years financial education has focused on the power of the equation to explain economic and financial forces. This distillation of complex forces into faux objectivity has created dangerous errors in financial understanding.

That objectivity has only been attained with the use of assumptions which do not hold in the real world. The Library of Mistakes exists to allow students, professionals and members of the general public to study financial history to understand how finance has worked, rather than how it should work if key unrealistic assumptions are made.”

http://www.libraryofmistakes.com/about

A searchable library of mistakes, errors, and failures is a precious resource for all students of economics.

If only such a library existed for students of deception.

I have only ever encountered one openly published systematic review of deception failures. This was a report produced by Barton Whaley in 2010 for the US Foreign Denial & Deception Committee, entitled ‘When Deception Fails: The Theory Of Outs’. It presents a taxonomy of the causes of deceptive failure, illustrated with 60 examples of failure in military and intelligence deception operations. The report was later incorporated in Whaley’s posthumously published book, ‘Turnabout and Deception’ (2016, pp.IIi-II90).

Failed deception provides an incredible learning opportunity. It enables a postmortem study of the aetiology of failure. Analysing multiple failed cases enables the revelation of common causes and patterns of failure. And cutting the data in different ways can reveal how failure arises from the intersections between the target, environment, strategy, execution, and other factors. Of course, any analysis is only as good as the available historical case data, the analytical framework employed, and the skill and experience of the analyst.

Insights about the causes of failed deception enable enhanced target audience analysis (that could, for example, identify early warning signs of prospective failure), stronger deception planning processes, improved risk management, and better informed operational oversight and sign-off.

Given these benefits, it is surprising that there are not more published studies on deceptive failure. Do please let me know if you are aware of any others.

In 2017, the Library of Mistakes opened an international branch at FLAME University in Pune, India. And at present, the Edinburgh branch is closed in preparation for a significant expansion and reopening in Spring 2022.

Both activities suggest that there is success in failure!

References

Whaley, Barton. (2010). When Deception Fails: The Theory Of Outs. Washington, DC: Foreign Denial & Deception Committee. National Intelligence Center, Office of the Director of National Security.

Whaley, Barton. (2016). Turnabout and Deception: Crafting the Double-Cross and the Theory of Outs. Annapolis, Maryland: Naval Institute Press.

The Wink

By Simon Henderson on

A few years ago, I was scammed. I actually rather enjoyed it.

It was a weekday morning, and I was standing in a standing-room-only, personal-space-invading, hot-and-sweaty-tin-of-sardines train carriage.

I exited at London Charing Cross and was immediately engulfed by a surging confluence of passengers, all rushing inexorably towards the automated ticket barriers at the end of the platform. As the crowd neared the exit, it further compressed, slowing to an awkward shuffle that advanced just inches at a time.

The people-pressure-cooker behind the barrier created a constant flow of people through it. And the corresponding stream of tickets inserted into the machine meant that the barrier never fully closed. Occasionally, it would begin to close, then snap open with a loud thunk as the next person inserted their ticket.

As I reached the machine, I inserted my ticket. But this time, the previously ever-open barrier slammed shut. Simultaneously, the person who had, mere fractions of a second earlier, exited the barrier in front of me, looked over his shoulder and winked at me.

In an instant, I knew what had happened. The person in front had mimed putting his ticket into the machine (I realised I never saw his actual ticket) and then moved his body towards the open barrier. On autopilot, I inserted my ticket into the machine, causing it to stay open. This let the person in front through, and the barrier shut behind him. He had enjoyed a free rail journey, while I definitely was not enjoying its consequences.

With increasing panic, I retrieved my ticket and (in a pitiful public display of my innocence) inserted it again. A large red cross lit up the machine, publicly broadcasting my rejection. In the crush, exasperated eyes burned into the back of my head. It was a bloody nightmare.

I turned to face the baying, ever-deepening crowd, which I now blocked from exiting the platform. I began to fight my way against the raging tide, my weak smile breaking frequently to silently mouth an ever-so-British “sorry”.

I eventually made my way to a guard and explained what had happened. Without acknowledgment or even eye contact, he wearily inserted his card into the machine to let me through.

At the time, this experience was exasperating.

So, I was caught off-guard by the rush of delight that subsequently flooded my senses.

My scammer’s simulated insertion of his ticket into the machine and the choreographic timing of his approach to the barrier were poetry in motion. His cheeky wink and unerring confidence that the crowd would prevent me from ever catching him was the cherry on top of his perfectly executed scam cake.

I usually remark that the best scams leave no trace as to their existence. In this case, I am forced to make an exception.

Deceptive movement is critical to many forms of deception. It occurs in scams, magic, sports, illusions, art, special effects, casino cheating, military deception, and many other applications.

For a variety of interesting studies on deceptive movement, see:

And remember, if you ever find yourself standing in front of a crowded automatic barrier, do ensure that the person in front of you is clear before you insert your ticket!

Delphic Deception: Machine Learning and the Ethics of Deception

By Simon Henderson on

Why is it that whenever one finishes and submits any form of work, new information instantly comes to light that you wish you had had an opportunity to include?

I recently contributed a chapter on ‘Creativity and Morality in Deception’ to a book on Creativity and Morality that is currently in production by the University of Connecticut. Shortly after submitting the chapter, I discovered a site called Ask Delphi.

Delphi is a machine learning model produced by the Allen Institute for Artificial Intelligence (AI2). It has been trained to make ethical judgements about everyday questions and scenarios, based on ‘reading’ 1.7 million examples of people’s ethical views. Three human arbiters (that have passed various tests to screen out inherent biases) have further refined the system by saying whether they agree with the AI’s answers. The system then uses the majority or average conclusion to decide right from wrong.

AI2 claims that Delphi:

“… demonstrates the promise of language-based common-sense moral reasoning, with up to 92.1% accuracy vetted by humans.”

A paper describing the creation of Delphi can be found here.

I thought it would be interesting to see what Delphi made of various ethical dilemmas I address in my chapter. These draw from classical philosophy and more recent examples of pro-social deception.

Initially, I was surprised to discover that Delphi adopts an absolutist position on several fundamental ethical questions about deception. In this respect, its views are consistent with philosophers such as Augustine, Aquinas, Kant, and Sartre, who argued that deception is always wrong and that there can be absolutely no exceptions.

Here is how Delphi answered:

“Is it ever ethical to deceive another person?”
– It’s wrong

“Is it ethical to deceive another person if the person benefits from that deception?
– It’s wrong

“Is it ethical to deceive a deceiver?”
– It’s wrong

I then found that Delphi (apparently) supports Plato’s concept of the Noble Lie (i.e., a lie told to benefit others) which entirely undermines its absolutist position:

“Is it ethical for somebody to tell a noble lie?”
– It’s okay

“Is it ethical to lie for benevolent ends?”
– It’s okay

Delphi also appears to agree with a range of utilitarian and consequentialist philosophical perspectives on deception, which advocate that deception is sometimes legitimate, desirable, and even necessary:

“Is it ethical to deceive a person if it saves their life?”
– It’s okay

Is it ethical to deceive one person to save the life of another?”
– It’s okay

Further, Delphi appears able to recognise and differentiate between malevolent and benevolent applications of deception. In some cases, its answers were nuanced and insightful.

“Is it ethical to scam another person?”
– It’s wrong

“Is it ethical to mimic the signature characteristics of another brand?”
– It’s wrong

“Is it ethical to lie to spare another’s embarrassment?”
– It’s okay

‘Is it ethical to protect a computer network by deceiving prospective attackers?”
– It’s okay

“Is it ethical for a magician to use deception to entertain her audience?”
– It’s expected

“Is it ethical for a military commander to deceive his or her enemy?”
– It’s expected

“Is it ethical to deceive mosquitos to slow the spread of malaria?”
– Yes, it is ethical

“Is it ethical to use decoy molecules to deceive cancer into slowing its spread?”
– It’s good

The one exception I found to Delphi’s positive disposition towards benevolent deception relates to storytelling:

“Is it ethical for a work of fiction to deceive its readers?”
– It’s wrong

Note that Delphi allows questioners to provide feedback on its answers and record their rationale for any disagreement. I made sure to register my various points of contention, hoping that, with more time and data, the system will eventually update some of its more questionable and contradictory answers.

By accumulating more case data and associated human feedback, I believe that Delphi could become a reasonably reliable system for answering ethical questions about deception. However, deception and related concepts such as the truth, lies, and paltering are complex constructs when one begins to unpack their meaning. And, in common with all AI, until Delphi can explain the rationale underpinning its judgements, users will have no basis to establish trust or reliance in the system.

For promising work on the future of Explainable AI (XAI), that has the potential to improve dramatically users’ trust in systems like Delphi, see Hoffman, Klein & Mueller (2018) and Hoffman, Mueller, Klein & Litman (2018).

References

Hoffman, R. R., Klein, G. & Mueller, S. T. (2018). Explaining Explanation for “Explainable AI”. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 62(1). 197-201

Hoffman, R. R., Mueller, S. T., Klein, G. & Litman, J. (2018). Metrics for Explainable AI: Challenges and Prospects. arXiv:1812.04608

Deception Offstage: Applying Magic to the Military

By Simon Henderson on

It was a pleasure to speak recently at the Science of Magic Association (SOMA) seminar on Deception Offstage.

I shared the podium alongside:

  • Professor Patricia Kingori at Oxford University who studies the ethical experiences of frontline workers in global health (and who has a podcast on Genuine Fakes).
  • Professor Koen Peters who heads the Socio-ecological Health Research Unit at the Institute of Tropical Medicine in Antwerp.
  • And magician and scam expert Brian Brushwood (who has an excellent podcast on Operation Mincemeat).

The seminar addressed two questions:

  1. Beyond entertainment, can techniques developed for magical deception be used for social good?
  2. Can concepts derived from magic and deception be useful in areas such as public health and security?

I spoke about the contribution of magic to defence and security.

The session is available to view on YouTube or below:

Dead Dogs, Viking Treasure, and the Einstellung Effect

By Simon Henderson on

If you want to hide a dead body, you might consider burying it six feet underground, with a dead dog buried directly above it at a more shallow depth. This way, when sniffer dogs lead investigators to the burial site, subsequent exploration will uncover the dead dog. This discovery helps explain away the sniffer dog’s indications and will likely terminate the investigator’s search process.

The Dead Dog Strategy is a variation of the Einstellung Effect, in we seek to establish solutions to problems as efficiently as possible. Giving searchers what they are looking for is one means to stop them from searching further. After all, why would you continue to expend energy searching for something you have already found?

I recently came across an example of the Dead Dog Strategy at an exhibition of the Galloway Hoard, a collection of some of the rarest and most unique Viking-age objects ever found in the UK.

Selection of objects from the Galloway Hoard (National Museums of Scotland, 2021. CC BY-SA 4.0).

The Hoard was buried in two distinct layers. The first comprised a decoy layer of silver bullion and an Anglo-Saxon cross. Hidden beneath this was another layer that contained more than double the quantity of silver, a box of objects made from gold, and a lidded, silver-gilt vessel that held a remarkable collection of jewellery.

The Dead Dog Strategy in the burial of Viking treasure.

Essential characteristics that make the Dead Dog strategy effective include:

  • The decoy is of sufficient payoff that it is credible.
  • The target has to work to acquire the decoy.
  • The physical or cognitive distance between the decoy and the prize is sufficient to discourage further searching.

The Dead Dog strategy has applications in areas such as cyber defence, diamond transportation, sacrificial moves in chess, false solutions in magic, and dummy endings in works of fiction.

Design Thinking for Cyber Deception

By Simon Henderson on

The past decade has seen an explosion in the number of vendors supplying cyber defence systems based on deception. The majority of these systems generate adaptive decoy networks and assets that lure attackers into increasing the time they spend exploring and analysing the (false) networks they attack. Meanwhile, covert instrumentation collects data about the attacker’s capabilities and methods, leading to actionable threat intelligence that can inform the design of stronger defences.

The breadth of deception reflected in these systems is usually limited. Most employ mimicry to portray false networks and assets, and use masking or repackaging to conceal their instrumentation. Seemingly, the more expansive set of deceptive strategies that defenders could potentially use to manipulate attackers (and their tools) remains unexplored.

The multitude of suppliers gravitating towards a common and limited set of deceptive strategies perhaps suggests a lack of awareness about the true scope of opportunities that deception provides. How, then, might cyber defenders innovate to generate a broader repertoire of deceptive measures to counter attackers? There are many approaches, but one that is often highly effective is to seek inspiration from the patterns of deception that occur in other (non-cyber) domains.

At the beginning of 2021, I participated in a design thinking workshop organised by Professor Debi Ashenden (University of Adelaide), Robert Black (Cranfield University), and Iain Reid (University of Portsmouth) that explored how deception in other disciplines can provoke the design of new forms of deceptive network defence.

Provocations included:

  • Japanese castle defences.
  • Code ‘smells’ in software engineering.
  • Sliding doors.
  • Gang graffiti and tagging.
  • The plot of an Indiana Jones action-adventure film
  • Deception for physical safety.

Workshop participants came from academia, government, a cyber deception technology company and independent defence and security experts. Topics addressed included risks, opportunities, and threats; measures of success; and limitations. The workshop resulted in a journey map that detailed considerations for operationalising cyber deception based on techniques drawn from other contexts.

A paper describing the workshop and its outputs was presented at the 54th Hawaii International Conference on System Sciences (2021) and is available here.

Used Poppies, Magic, and Deceptive Thinking

By Simon Henderson on

I spend a great deal of my time studying where deceptive thinking comes from. I am fascinated by questions such as:

  • Are some people naturally good at deception (and if so, why)?
  • What do good deceivers think about when they’re formulating deception?
  • Can deception be learned (and can it be taught)?
  • Can methods and tools help amplify the rigour and potency of deceptive thinking?

One insightful approach that has shed some light on these questions has, somewhat surprisingly, been to study my own thinking — how do I formulate deceptive action?

Here’s one example.

Used Poppies is an ESP-like magic effect with playing cards that I originally published in 2017 (Henderson, 2017).

The effect plays out as follows:

The performer hands the spectator a regular deck of cards and invites them to inspect and shuffle it. The spectator then removes two runs of cards from ace to five — one in red suits, the other in black.

The performer then turns their back to the spectator and genuinely cannot see their actions. The spectator mixes the cards, deals them into two piles, and then deals each pile to form a line – one for them and one for the performer. At this point, the performer turns around to face the spectator again.

Despite genuinely not knowing the identity or position of any of the cards, the performer seemingly begins to ‘sense’ their values. Slowly, they place each of their cards onto one of the spectator’s cards to form a series of pairs. The spectator turns over the cards to find that each pair comprises a red card and a black card of the same value.

If you want to skip the background behind creating this effect and go straight to learning it, see here.

I created Used Poppies while studying the stock shuffling systems of Erdnase (1902, p.65-76) and Hugard and Braue (1940, p.73-75). Stock shuffling involves moving predetermined cards into specific locations in the deck via the act of shuffling. The deck is thereby stacked to ensure that these predetermined cards fall to a given player during the next round of dealing.

However, the technique is complex, awkward, and is tough to master such that it looks natural. When I first learned stock shuffling, I turned the deck face up so I could see (and not have to imagine) how various cuts, jogs, breaks, throw-offs, and shuffles acted to rearrange the cards.

I then began to study other ways to mix cards while keeping them face-up. For example, I experimented with simple stacked packets (e.g., in numerical order) comprising just a few cards so I could easily track their distribution while dealing.

At some point, I discovered that alternate dealing a stack into two piles results in pairs of cards always falling into the same relative (knowable) positions. Technically, alternate dealing a cyclic stacked packet creates positional sequences in the resultant piles that have a fixed offset between them. Cutting the stack prior to dealing does not affect the offset.

On this basis, I soon developed a guaranteed process for knowing the locations of pairs of cards in face-down packets that a spectator had previously cut and dealt. With further experimentation (and a fair degree of road testing) the effect coalesced into its current form.

The strands of deceptive thinking that led to the creation of Used Poppies included:

  • Studying, researching and trying out an existing (documented) deception strategy.
  • Curiosity about the underlying operational basis on which the strategy relied.
  • Experimentation that led me to apply the same principle differently (transitioning from assembling a stock via shuffling to studying how dealing distributes a retained stock).
  • Noticing a recurring pattern and recognising its broader utility.
  • Construction of a presentational story that contextualised, justified, and help obfuscate the method.
  • Experimenting, rehearsing and receiving feedback in a safe space.
  • Field execution (i.e. performance) and evaluation, leading to further refinement.

These activities are fundamental to all deceptive thinking and apply to any problem where deception might provide a viable solution.

A full description of Used Poppies and an explanation of its underlying method can be found here.

References

Erdnase, S. (1902). The Expert at the Card Table (Artifice, Ruse and Subterfuge at the Card Table: A Treatise on the Science and Art of Manipulating Cards). Frederick J Drake & Co.

Henderson, S. (2017). Used Poppies. Psycrecy: The Society of Mystery Entertainers, 2(3), 94-104.

Hugard, J., & Braue, F. (1940). Expert Card Technique. C. W. Jones.

Learning From Fake News Games

By Simon Henderson on

“We are all apprentices in a craft where no one ever becomes a master.”

(Hemingway, 1961)

Social media has brought about an attention economy in which polarisation, extremism, and conflict are now the primary factors that attract the public’s fleeting concentration. Since the 2016 US elections, there has been an explosion in the proliferation of online fake news, misinformation, and disinformation. Actions taken during President Trump’s administration, the worsening climate emergency, and the emergence of the global COVID-19 pandemic have further reinforced an information landscape where fragile truths are increasingly hard to discern from forceful falsehoods.

Many initiatives are now attempting to tackle fake news. These include systems to automate the identification of fake news, automatic and crowd-sourced fact-checking and labelling systems, methods to seek out and provide alternative viewpoints, legislation of social media platforms, and a wide variety of educational initiatives.

One exciting development is the emergence of educational games that engage the public in learning about fake news in novel and interesting ways. While ostensibly functioning as entertainment, these games also serve more serious goals, echoing the sentiments of Scarfe (1962):

“The highest form of research is essentially play.”

Scarfe (1962)

In a new article here, I discuss ten online free-to-play games that seek to address fake news. I address the theory behind how these games work and consider each game’s strengths and weaknesses. The games discussed are:

While all of these games support the battle against fake news, there are some notable gaps in the issues they address. Future games could, for example, consider incorporating strategic campaigns that are coordinated across multiple platforms, adversarial competition between fake news and counter-fake news activities, opportunities for the player to learn valuable lessons from campaign failures, and in-game capabilities to respond to fake news.

Where current games succeed, however, is in enabling the public to learn more about the complex (and not always stimulating!) topic of fake news in simple, engaging, and entertaining ways.

The full article can be read here.

References

Hemingway, E. (1961, 11th July). About Hemingway. New York Journal American.

Scarfe, N. V. (1962). Play Is Education. Childhood Education, 39(3), 117-121.

 

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