• Design research and thinking - how we understand creativity, innovation, change, and our dependency on goods
• Long-term social and cultural modeling
• Participatory and cocreative media
• Collaborative networks
• Short video on design thinking
• The future of personal mobility
• Design Thinking (one hour video)

What we learned

• Computation does not replace field work. Technology should not distract from the problem that one has to solve. First comes the problem, then the technology.

What we learned

• Introduction to computational social science (first chapter)
• Notation is essential to organize knowledge in a proper systematic way, e.g. Unified Modeling Language
• Collaborative technology is needed for social-science researchers
• Time-series analysis can discover underlying dynamics in interactions
• Game theory has contributed significantly to computational peace studies

What we learned

• Non-violent communication, founded by Marshall Rosenberg
• Replika is a chatbot that learns your chat style so it can mimic your online behavior (a "memorial" chatbot because it can even replicate a dead person). This can be used to clone your own style of communication, and show you how you appear to others.
• There is a whole branch of AI, sentiment analysis, that studies the "mood" of a sentence.
• An AI could potentially "correct" the emails/chats that you are typing and translate your rude style into a more empathetic style.
• The very first AI chatbot, ELIZA, was an empathizer.
• At the same time empathy can be weaponized (Cambridge Analytics learned to empathize with social-media users and exploited them)
• Empathy can arise from the direct experience of somebody else's reality.
• Technology should start by empathizing with users: empathy of communicating with the computer, with the user's needs. If the user interface cannot empathize with its user, how can we trust that the software will create empathy among users.
• The mediating technology has to behave like a monk: interpret the views of the two parties in a conflict at a higher level of abstraction.
• Piero's counter-argument: conflict is more monetizable than no-conflict, therefore there is a vested economic interest in creating and amplifying conflict. Conflict is addiction like tobacco and pollutant like industrial pollution. There is an economic value in the addiction and pollution of conflict.
• Technology creates echo chambers that increase conflict. We need technology that will reward the opposite of the echo chamber: listening to other's views.
• We need technology that can promote empathy as a socially desirable role like "no smoking" and "recycle".
• Piero's counter-argument. Social-media platforms need to monetize the social interactions, and therefore their algorithms will propagate both real and fake news if they generate revenues. The algorithm cannot distinguish between real and fake, but it can easily count revenues. What is true on a social-media platform is what makes money for that platform.
• Trust is vulnerable. Trust generates revenues: consumers read reviews and are influenced by them. Therefore businesses are interested in twisting those reviews to their advantage. Firms that control those reviews are under pressure to accept "bribes" to alter the visibility of positive reviews. Review platforms can become extortion platforms: "pay a fee and we'll push positive reviews to the top, cancel and we'll push the negative reviews to the top". There is economic pressure to break any trust system.

What we learned

• Functional integration leads to trust.
• Conflict arises from a mixmatch among people, resources, boundaries.
• Political devolution/fragmentation (the number of countries quadrupled since 1945) has increased chances of conflict.
• Connectivity overcomes the conflict.
• Transnational infrastructure of connectivity: transportation, energy, communication
• This transnational infrastructure changes the incentives of political groups: a country may spend money to support the currencies of other countries currencies, countries may share the same electrical grid, etc
• Initiatives like the new Silk Road become marketplaces for transnational governance.
• Rise of functional geography (Internet, telephony, oil pipelines) on top of physical geography.
• Indirectly, the process of political devolution/fragmentation causes the disappearance of autarchy
• Connectivity physically embeds interdependent governance of transnational infrastructure
• A new layer of bureaucracy

What we learned

• Normativity: social technology for coordinating people
• Conflicts arise when norms collide
• Norms change when we "encounter" the other
• Technology for peace would be a technology that helps "de-otherize" the other
• We tend to demonize those outside our circle, the "other". Technology for peace should expand that circle and induce global solidarity.
• Social life has three stages: rejection (eg homophobia), begrudging tolerance (e.g., heteronormative) and positive affirmation
• Normative structures that foster collaboration (not just coordination) are those that induce a transition from tolerance to affirmation
• The "thorough normative community" is one in which the rational powers of one are resources for all.
• The Symbolic Systems Program trains the technology leaders of the future: it is liberal arts for the 21st century. We under-educate technology leaders.
• Technology is just a tool. It operates in a society shaped by norms. Technology affords opportunities, elicits behavior. Technology is an "independent pressure point". It is both a constraint and an enabler.
• To deal with complex problems we need to redesign civil society.
• Paper: "Where norms come from"

What we learned

• Think of other individuals as individuals
• Technology can boost peace if it helps empathize with the lives of others: a stranger is an individual just like you
• Drone operators who follow and kill terrorists remotely suffer from PTSD just like foot soldiers because they get to know the terrorist as an individual as they follow his daily life
• Immersive technology versus anonymity technology (statistics)
• Technology that makes people more familiar with the other rather than technology the simply invades people's lives
• Technology that foster cultural translation, so that people can appreciate, value and respect each other's symbols
• Wisdom of the crowd
• Watch: C-span inteview about his book "Behave"
• Read: "Why your brain hates other people"

What we learned

• Humans are designers, they design things
• Design is about measuring feedback
• There are seven basic measurements in the hard sciences: what are the basic measurements of innovation?
• The design coach, who guides the designers (e.g., the venture capitalist)
• Entrepreneurs are storytellers
• PIl designs a good that is positive engagement
• PIL designs systematic innovation
• Someone else's interview: An interview

• His article on "The New Economics of Innovation Ecosystems " (quote: "Trust, particularly between diverse strangers, can influence standards of living")

What we learned

• Intractable conflicts are conflicts in which each party thinks that success by the other party would threaten survival. They are existential conflicts.
• Two main factors cause conflict: competing interests and threats to identity
• Conflicts may escalate due to irrational distrust (distrust that causes both to lose)
• The barrier: the "enemy" relationship, not just adversarial relationship (the enemy is demonized)
• What modality of presenting data would be pro-social?
• Peace and Justice: just causes for going to war; just conduct in war (eg, prisoners of war); just aims of war (inconditional surrender? withdrawal?); just post-war behavior (reparations? reconstruction?)
• Conflict resolution = achievement of a mutually bearable shared future
• Strategy for conflict resolution: each party should try and articulate the other party's narrative
• Technology doesn't help when it simply create an echo chamber. Technology may stir more conflict than reconciliation.
• Lee Ross: Barriers to Conflict Resolution
• Lee Ross: Relationships between Adversaries

What we learned

• He had access to a large dataset of chats (project Citizen Mindscapes managed by Krista Lagus ). This is an interesting case study: the data are qualitative, not quantitative.
• Piero's thoughts (not verbatim what Gote said): P
• P: The issue is how to turn qualitative data (noncomputational) into quantitative data (computational)
• P: We need a methodology to tag the chats so that they can be fed into a computer.
• P: Then we need an algorithm to identify the signal of conflict in a chat or group of chats (disagreement is not conflict: when does it become conflict?)
• P: Then we need an algorithm to determine if the conflict is increasing or decreasing over time between those two people
• P: The algorithm may be able to prevent conflict: which pattern of conversation is likely to end in conflict?
• P: The algorithm should also be able to calculate, based on something like pattern recognition, which action can reduce the chance of conflict
• P: The problem is that the algorithm has to be customized for each person because each person has different behavior in the face of disagreement.
• P: The goal is a phase transition to a balanced state in which the perception of the self and the perception of the other are in equilibrium.
• Nyman: The individual has to realize that we are in a permanent state of entanglement (like in quantum mechanics).
• Nyman: It is important to model networks at different levels because we are connected in multiple ways to others
• If we cannot represent the ways in which people connect, we cannot understand their conflicts, prevent them, solve them.
• Peace = relationships among people
• The relationships/connections are also dynamic (change over time), not static.
• Application of peace methodology: crisis management (done by "peace negotiators")
• Piero: conflict is a reaction, not an action, which then becomes an interaction
• Piero thinks that conflict in conversation can be due to several different levels of lack of information: hard data may be missing (eg an argument about how many votes you got in a presidential election), statistics may be missing (eg an argument about older people voting for conservative candidates), reputable sources may be missing (eg quoting a scientist in an argument about climate change), the broader context may be missing (is the USA good or bad for peace?).

What we learned

• Background in science (mathematical psychology and neural networks), not in art
• Human-centered design requires a deep understanding of people
• The transition to a sustainable society will require new ways of designing that are informed by a deep understanding of local ecosystems and culture.
• DesignX (the future of design): design for complex sociotechnical systems ("nine properties, divided into three categories, that characterize DesignX problems")
• The problem of design is not understanding/modeling the issues but implementing the solutions. Most design results in great ideas but has no last effect on society/firms.
• Political, economic, cultural, organizational, and structural issues hamper implementation.
• His critique of dschool and IDEO: design doing vs design thinking
• His role model for implementation: political scientist Charles Lindblom, founder of the theory of "incrementalism" ("The Science Of 'Muddling Through'", 1959)
• Eric von Hippel (MIT Sloan School of Management): practical methods that individuals, open user communities, and firms can apply to improve their innovation development processes
• New lab at UC San Diego, which is basically a people-centered citizen-science project to solve complex intractable social problems
• Norman and Tognazzini: "Apple is destroying design" (2015)
• his website and the Design Lab's website
• Read the first chapter of "Living with Complexity"
• Read excerpts from "The Design of Everyday Things"
• Read Essay on "Simplicity Is Not the Answer"
• Reviews of his book "Living with Complexity"
• Reviews of his book "The Design of Everyday Things"
• Watch The three ways that good design makes you happy (TED Talk)
• Watch Thoughtful Design
• Watch Video1 on "Living with Complexity"
• Watch Video2 on "Living With Complexity "
• Watch Video3 on "Living With Complexity "
• Listen Interview on "Living With Complexity "

What we learned

• First time in history we have data on individual-to-individual interactions because computing technology mediates interactions
• We can design online "field" experiments
• we cannot remove risk from interactions but we can minimize it
• Reputation and trust are contextualized: they don't automatically transfer to other domains
• Reputation platforms can also overcome biases
• Trust is required when there is risk. Blockchain, for example, is not about trust but about coordination.
• Potential danger of reputation platforms: too much information about strangers creates weaker social ties (no need to be real friends)
• Piero: What is the difference between recommendation algorithms (that create "trust" between a consumer and a brand) and trust algorithms? They both facilitate interactions among strangers, measure behavior, and result in a financial transaction. The only difference is that the trust algorithm broadcasts your reputation to everybody.
• Lecture on trust
• Joe Gebbia's TED talk How we design for trust
• Paper with Karen Cook: Online Field Experiment

What we learned

• Full text of the interview
• A language for innovation that they call Interactions Dynamics Notation
• paper
• How to model interaction between people
• Division of labor for innovation ('venture development')
• Exploring the relationship among technology, society and business
• New methods of developing ecosystems of innovation
• Innovation ecosystem = team collaboration
• A factory that produces 100s of startups
• Discover the needs of a city and model them
• The city is a living organism: needs change, tech changes
• Cooperative design thinking
• John Arnold at Stanford (1959) taught creativity to engineers and formed a design group https://blog.rwth-aachen.de/designthinking/2016/01/30/design-thinking-history-the-impact-of-stanford-prof-john-arnold/
• The behaviorial side of innovation: how do teams get together to create innovation
• Recipe model vs No-recipe model (when the recipe is not relevant anymore)
• "Invent" is the no-recipe model, inventing is about generating new ideas, and this is what great design teams do
• IDN is the notation to describe this project
• Influenced by cognitive semiotics, Ade Mabogunje's Real-time Venture Design Lab program (ReVeL), and by Leonard Talmy's "Force Dynamics in Language and Cognition" (1988)
• Summary of Force Dynamics: http://cogweb.ucla.edu/CogSci/Talmy.html
• Force Dynamics was a visual language for narratives
• Eg, sustainable entrepreneurship: generate new ideas and experience, learn from failures
• detour: consequence-driven logic vs identity-based logic (great visionary leaders are driven by values) - see James March choo.fis.utoronto.ca/fis/courses/lis2176/Readings/march.pdf
• But also very influenced by improvisational theater and jazz improvisation
• In 2011 Sonalkar adapted it to interaction: response-based (what is the response of the other members of the team to an idea) and capture visually the dynamics of interaction
• Lucy Suchman http://www.wikiwand.com/en/Lucy_Suchman studied user behavior at Xerox PARC (she wrote The problem of human-machine
• communication in 1985 www.lancaster.ac.uk/fass/doc_library/sociology/suchman_cv.pdf republished in 2007 with additional chapters) and then came to Stanford to study design behavior
• IDN+Machine Learning = best practices of interaction (or at least interaction patterns)
• He is willing to write a chapter of the book

What we learned

• Game design thinking is the intersection of game-design science, behavior design, and neuroscience
• MDAO framework: mechanics -> dynamics -> aesthetics -> outcome but played in reverse: first define the outcomes, then derive the aesthetics (what would engage the player, stimulate her emotions), then select the appropriate mechanics
• Skeptic on the use of design thinking, hence neuroscience: intrinsic motivation is driven by emotions and it is now possible to measure brain activity
• The purpose of prototyping is to make it fail and then study why it failed
• Gamification failed

What we learned

• Jinxia's summary
• Cooperation class
• Cooperation notes
• Technologies of Cooperation report
• Cooperation Commons

What we learned

• Steve Dow's Stanford talk of May 2017
• Critique of design as an individual endeavour: the community has to participate. Design thinking + Crowdsourcing.
• We need design practices and technology to support the creativity of crowds. We need to teach design effectively to the general public and motivate the public to participate in solving their problems.
• Improving crowd innovation with expert facilitation
• More interested in qualitative data than quantitative ones: interviews are the main tool. Tag salient moments in the interview. Generate metadata for analysis. Emphasize different perspectives. Possibly also self-interviews.
• His pilot project is the students interviewing other students: June 9 is the presentation. Then they will roll out a project for the city: an innovation challenge. Call for innovation ideas. Interviews will be collected throughout the summer and presented at a October 26 city event organized by Don Norman. He should have preliminary results at the end of September that he is willing to share.
• His approach could apply to peace innovation because it focuses on: exposing people to other points of view; visualizing the crux of the conflict; consensus building.

What we learned

• Full text of the interview
• Cities are always unfinished and incomplete projects
• Work on a local challenge in order to engage citizens who have a vested interested in finding a solution
• She had no peace data because of the political challenge to collect data (European Union restrictions on data sharing)
• City labs need a clear contract from Stanford. Without a contract the city lab is liable when using the Stanford name.
• We need to create sustainable and replicable citizens platforms
• But skeptic about open innovation platforms that don't involve face-to-face interaction: the quality of the conversation and of education tends to be low, and the degree of engagement by the participants tends to be low
• Open IDEO seems to be the only open innovation platform with critical mass
• Nobody else working on the triangle of Tech, Innovation and Peace but schools of human-centered design like the Hasso Plattner Institute of Design indirectly train students to work in that space

What we learned

• Do the new mediating technologies increase polarization? Manuela is studying the negative effects of mediating technologies.
• Manuela disagrees with the "contact hypothesis", or Intergroup Contact Theory. The contact hypothesis says that the best way to improve relations among groups that are experiencing conflict is for them to have contacts. This theory originated with Gordon Allport's "The Nature of Prejudice" (1954). Studies such as the one by Thomas Pettigrew and Linda Tropp (2000: 94% of the time conflict diminishes as intergroup contact increase) lent it credence.
• Piero: we value competition (a society where everybody does the same thing and has the same life would be pretty boring). But competition is the beginning of conflict. How do we achieve cooperation in societies that promote competition? If evolution is a struggle for survival, why are we still capable of altruism? Manuela: institutions should control competition.

What we learned

• A lengthy summary of the two conversations
• Definition of social mess
• A reading list of interesting messes
• A discussion on state transition phases (Piero's email to Mark): A problem does not exist in a vacuum: it is usually an element of a bigger context, in which one problem influences many other. Operating on the individual problem affects all connected problems. In many cases the correct approach is to work on all problems at the same time, reorganizing the whole rather than simply replacing a defective part. In such cases the solution consists in a phase transition, from one state of equilibrium to a new one. When the phase transition takes place, the solution has become more sustainable. Compare with your cybernetic loop: when does it end? Bob was asking: what are the indicators that you use to decide that you reached a sustainable state of peace? In a sense your cybernetic loop should be multidimensional, an intricate 3D loop resembling a multilayered neural network. A different mathematical way to express this concept is to imagine that peace if a nonlinear function f(x) that we want to maximize. Often the only practical way to work on a nonlinear system is to use some simulation method. It turns out that neural networks are universal simulators (proven independently in 1989 by George Cybenko and Kurt Hornik) i.e. de facto what they do is: to maximize a function. Not sure what the bottom line is (still thinking) but there might be a correlation between an extended version of your cybernetic loop, transition phases in physics, and neural networks.

What we learned

See Book outline

What we learned

• Full text of the interview
• See Book outline

What we learned

• Can technology measure and improve peace?
• Cooperative Design Thinking in Peace Innovation
• Mark Nelson's and Robert Horn's conversation about the "Peace Design Loop"
• See Book outline