Model: praisethefool/human_tech-fields-multilabelclassifier
Author: praisethefool
Pipeline: text-classification
Library: setfit
Tags: setfit, safetensors, mpnet, sentence-transformers, text-classification, generated_from_setfit_trainer, arxiv:2209.11055, base_model:sentence-transformers/paraphrase-mpnet-base-v2, base_model:finetune:sentence-transformers/paraphrase-mpnet-base-v2, model-index, region:us
Base models (finetune): id: sentence-transformers/paraphrase-mpnet-base-v2
Card metadata: tags: setfit, sentence-transformers, text-classification, generated_from_setfit_trainer
widget: Untangle Solving problems with fuzzy constraints Untangle Solving problems with fuzzy constraints Szymon Kaliski Marcel Goethals Mike Kluev January 2023 Have you ever needed to find a time for all your friends to meet for dinner or to create a seating plan for wedding guests These are examples of problems that require navigating a set of overlapping constraints you are only available on every other Tuesday or Thursday Chris will not show up if Ash is not there but Ash is in town only the last week of November and you really wanted to catch up with Chris We often work out problems like this with a pencil and paper experimenting until we find a solution but it feels like computers should be the perfect tool to help us In fact there are programming tools called theorem provers which are designed to solve exactly this class of problems They excel at helping experts work through fullyspecified problems with a clear solution Unfortunately we rarely have a formal understanding of our problems We come to understand them interactively by trying to find a solution In fact we often just need a solution that is good enough instead of one proven to be optimal We set out to experiment with interactive computerassistance for this type of thinking Untangle is a research prototype that helps you think through everyday constraint problems using your tablet stylus With Untangle you leave handdrawn marks on a page sketch out the representation of your problem introduce constraints graphically and browse through sets of possible solutions This work was presented as a part of our Programmable Ink talk at Strange Loop 2022 We welcome your feedback inkandswitch or helloinkandswitchcom Contents Thinking fuzziness and constraints Design principles Inspirations Logic programming Pattern matching Graphical production systems Realworld applications of logic programming Untangle Assignment problem Frequency assignment bids Coffee shop schedule Generative art Recursive rewrites Findings A smooth ramp from concrete to abstract helps form intuitions about the system Informal solving is most useful for certain kinds of problems Many problem representations look like tables Handdrawn input is well aligned with exploratory problemsolving Fuzziness and live feedback contribute to a conversational feel Shortcomings The system lacks clear semantics Turning ink into symbols is an unnecessary technical crutch Some parts of the system lack visibility Responses from the computer are underdesigned Small canvas artificially constrains the problem representation There is no way to explore the solution space Conclusions Thinking fuzziness and constraints Computers can be great at solving logic problems like the ones mentioned above as long as we can describe them in a formally correct and detailed way Special programming languages and techniques—theorem provers—exist and can calculate solutions for huge datasets These languages are most often used by mathematicians to help with proving formal theorems or by domain experts to aid in modeling large scale industrial production systems A Constraint satisfaction problem can be solved using logic programming techniques such as Satisfiability Modulo Theories SMT or Answer Set Programming ASP These programming languages are useful after we have encoded a problem in machinereadable form but first we must do the harder part fully understand the problem For this we often reach for pen and paper which allows us to think fuzzily and omit various levels of detail when problemsolving We can quickly sketch out the representation of the problem without worrying about absolute correctness For a sampling of realworld pen paper constraint problem representations have a look at How People Visually Represent Discrete Constraint Problems by Xu Zhu et al This project explores what it might look like if computers could support this style of earlystage thinking Untangle is specifically not a tool for solving artificial logic puzzles nor is it a tool for creating formal specifications for industrial systems Instead we are interested in a tool that can help us think through illdefined problems understand compromises and learn about what kind of questions to ask Untangle is a continuation of the threads highlighted in the thinking modeling and computers section of the Crosscut essay Mainly we want a tool in which we can sketch a dynamic representation of the problem at hand and have a conversation with it Design principles Keep focus on the problem not the implementationWe want a tool in which your focus remains on the problem at hand as much as possible rather than thinking about the correct way to encode it in a machinereadable way No errors undefined values or unknown parameters to fill inThe tool should never block freeze or become unresponsive even if the user creates invalid states such as errors or incomplete input A wrong answer is better than no answer Everything is visibleBoth the domain model and the constraints should always be visible and interactive Conversation with the material is be encouragedWe want an iterative approach to problem solving—one where observing leads to thinking which leads to acting which leads back to observing You should be able to intuit connections between various rules and constraints by wiggling them and seeing other things wobble We also adopted most of the design principles from Crosscut A tablet stylus can become dynamic pen paper The content of what you are working on is the most important thing You should not have to use an onscreen keyboard for programming This is a personal thinking space Untangle shares a lot of context with Crosscut a research project in which we explored an approach to building dynamic models by direct manipulation There is one important design difference from Crosscut using handdrawn strokes instead of vector graphics We believe there is something special about leaving distinctively human marks on the page with a stylus so we want to go back to handdrawn marks like with Inkbase but with an entirely different computational model Inspirations Logic programming Logic programming is an important paradigm in computer science It is based on formal logic and allows programmers to describe problems using declarative statements “every human is mortal” and ask questions based on these statements “X is human is X mortal” Some notable logic programming languages include Prolog one of the first logic programming languages widely used for theorem proving term rewriting automated planning Z3 Theorem Prover a satisfiability modulo theories SMT solver that is targeted at software verification and program analysis Untangle uses Z3 as a library for solving Alloy Analyzer Alloy is a language for describing and exploring software models It has been used in a wide range of applications from finding holes in security mechanisms to designing telephone switching networks Of particular interest is Alloy’s IDE that visualizes a possible structure based on the constraints provided by the user Alloy Analyzer’s interactive solver visualization Pattern matching Untangle relies heavily on spatial queries—finding symbols on the page by their spatial relation to other known symbols—which were inspired by Regex a domainspecific language for describing search patterns in text Qualitative Spatial Reasoning a calculus which allows a machine to represent and reason about spatial entities without resorting to traditional quantitative techniques QSR is often used in GIS Geographic Information Systems for querying geographical data For more information on QSR check out A survey of qualitative spatial representations by Chen et al Graphical production systems Work on Untangle was also inspired by graphical production systems which use shape matching rules and graphical rewrites to describe computations Publications that guided our work Shape Grammars and the Generative Specification of Painting and Sculpture a seminal paper by Stiny and Gips introducing shape grammars New graphical reasoning models for understanding graphical interfaces a paper from Furnas introducing BICPICT a pixelrewriting graphical reasoning system Wave Function Collapse an approach for generating tile maps from a single example which influenced our thinking on using superposition as a mental model for working with multiple possible values Wave Function Collapse algorithm visualzation Figure by Maxim Gumin Realworld applications of logic programming Finally we were guided by various examples of using theorem provers for working through everyday problems How people visually represent discrete constraint problems Using linear programming GLPK for scheduling problems Tax planning with Z3 Theorem Prover A shared pinboard becomes a collaborative modeling tool to plan a dinner party Untangle We are now going to introduce Untangle a tool for working out realworld logic problems Assignment problem To explore the basic concepts of the tool we are going to look at an assignment problem imagine you are teaching a class it is the end of the semester and each student needs to submit a short paper about some topic You want students to grade each other so you have less work to do Let us see how Untangle can help us solve this problem This reallife problem comes from Joshua Horowitz thank you Josh In its most basic form Untangle allows you to automatically assign symbols to other symbols For example you can put Bob into a box by drawing an arrow between the text Bob and the box—Bob will now appear in pink inside the box A symbol is anything that appears on the canvas Symbols can be a single stroke or collections of strokes Assigning Bob to a box We can also assign multiple symbols to a box Untangle will now show that there are two possible assignments by showing two dots at the bottom of the screen We can scroll through the different solutions Bob and Eve Assigning multiple students to the same box There are six students in our class so we will write all of their names Instead of drawing six arrows we can use spatial queries to find elements on the canvas Using a spatial query to grab all of the student names Whenever we make a selection of symbols on the canvas a popup appears This popup suggests different spatial queries we can use to match our selection In this case it suggests that we could look for a vertical column of symbols starting with Bob Representation of a spatial query capturing a column of symbols starting with Bob We can place this query onto the canvas and use it as a shortcut to refer to all the symbols that match it The matching symbols are highlighted in the same color for additional visual feedback Untangle only ever places one symbol into each box Whenever there are multiple ways to assign symbols Untangle will generate multiple solutions but display only one The dots at the bottom of the screen indicate that there are alternative possible assignments We can get a sense of the different solutions by scrolling through them Solution switcher We want to assign a student to every other student so let us create an empty box next to every name Just like with the spatial query for a list of names we can create a query that simply looks for all boxes This generates all possible ways to assign one student to another one Using the all boxes query to assign every student to another student Currently students are sometimes assigned to grade themselves While students will surely be happy to do so as a teacher I would rather avoid this situation Let us add a rule that prevents students from grading themselves To do this we will add a third spatial query This query matches any box that has something to the left of it The question mark acts as a wildcard matching any symbol Using wildcard to capture something next to a box and make that something not equal to the contents of the box Finally we can draw an inequality constraint arrow This expresses that whatever ends up in the box cannot be the same as whatever symbol is on its left Bob can no longer grade Bob Inequality constraint Let us say we omitted a student when writing the original list of names Because we are using spatial queries to describe the column of student names we can easily extend the list Extending the student list with a new name The results update reactively It turns out that Bob and Claire have written papers about similar topics So it would be great if they grade each other We can ensure this by simply putting their names into the corresponding boxes and the system will adapt accordingly Forcing the assignment of Bob to Claire Again the system reacts with new results Frequency assignment bids To show a few more interesting properties of Untangle let us look at a different example—running frequency spectrum assignment bids The basic idea is that a specific radio frequency spectrum say 5G is divided into smaller parts and sold to various operators This reallife problem comes from William Taysom thank you William Let us start by modeling this problem There are three telephone companies telcos that are bidding on the frequency spectrum from 34 GHz to 42 GHz The spectrum is split into eight bands and the telcos can bid on individual bands Initial model of the spectrum assignment problem Just as in the student grading example we could use spatial queries to assign telcos randomly to bands in the spectrum Assigning operators to random bands of the available spectrum But this is not really how an auction works Instead telcos bid on a specific number of bands that they want to obtain For example Verizon might place a bid for four bands We can model this using a count modifier which limits the number of times a certain rule applies Using a count modifier to limit the assignment to four times Let us rearrange the canvas a bit and add some imaginary bids for each of the companies Modeling bids from all of the operators Some bands can be more valuable for example the middle bands often have less interference so a company may bit not just on a specific number of bands but also specific placement inside the spectrum To model this we can either draw an arrow directly to the specified band or simply drag a symbol in place We can guide the solver into a direction that we care about and it will respond immediately Constraining the solutionspace further by modeling bids on specific bands in the available spectrum The number of bids might not equal the number of available slots—an overconstrained system Using most solvers the result would be an error message that the constraints are unsatisfiable Instead of showing an error Untangle will attempt to generate a partially correct solution by ignoring some of the rules Arrows will turn red indicating that for the currently shown solution this rule is ignored Relaxing the overconstrained problem representation by ignoring some of the rules When having a conversation with the material hearing “no but what if…” is more encouraging than hearing just “no” The machine does not brake or scold at you for making a mistake but instead shows compromises and possible directions which in turn helps generate new ideas Finally companies sometimes bid specifically on a set of consecutive bands—rather than just bidding on four bands they want four bands in a row We can model this using a combination of spatial queries and counts Creating an assignment rule of four consecutive bands using a combination of spatial queries and count modifiers Coffee shop schedule In the following example we will show how to create a work schedule for a coffee shop An easy solution is to assign employees to random days but to make a good schedule everyone is happy with we need to consider employee availability To solve this problem we need to two dimensions First we list availability of the employees in the topleft corner For each day that an employee is available we draw an X For example Jim is available on Monday Wednesday and Friday In the bottom right we draw a simple empty schedule for the week Modeling the baristas availability Untangle has a special lookup spatial query that allows us to look up information in tablelike layouts In this case it matches columnrow pairs together whenever it finds an X Using the lookup spatial query on the availability table You can think of this as finding all the available people for each day Untangle will only generate solutions where the day and name are matched in the availability table Visualization of running the lookup spatial query We then create a spatial query to find all of the empty slots in the schedule using a something on left box on right query Spatial query using a wildcard symbol and a box to the right of it We only want to assign employees to days they are actually available To do this we bind the wildcard matches on days of the week We then use the names to fill in the boxes in the schedules Untangle will show us all possible schedules based employee availability Resulting coffee shop work schedules based on employee availability The proposed schedules often have people working two days in a row—something we might like to avoid We can set up a simple constraint to make sure no two boxes in a row hold the same value Constraining consecutive not to hold the same value It is worth noting that in this example technically all the information needed to solve the problem is already on the canvas However coming up with a valid solution still requires serious “System 2” level thinking shuffling around symbols in your head It feels great to have the system do this part for you System 1 System 2 is a dichotomy introduced by Daniel Kahneman in Thinking Fast and Slow System 1 describes fast intuitive loweffort thinking while System 2 is effortful and slow Generative art So far all the examples we looked at were about constraining the solution space—progressively going towards a small set of satisfying solutions This is only a one part of the problemsolving process which has two distinctive phases that feedback into each other—expanding and collapsing Expand and discover different possibilities then narrow scope and focus We can use Untangle’s primitives to force us to expand the possible solution space instead Let us illustrate this by recreating one of the most famous computer art pieces 10 PRINT 10 PRINT is a oneline Commodore 64 BASIC program that generates a visual pattern on the screen We can make a couple of boxes two symbols and fill all boxes Using spatial queries to fill all of the boxes with permutations of diagonal lines This already starts to look interesting but we can get to more compelling results by adding additional constraints Forcing more interesting results by applying inequality constraints And of course we can introduce additional symbols and keep exploring the solution space 10 PRINT variation using three symbols and two inequality constraints Recursive rewrites We can apply the rewrites recursively by flattening the pink results back onto the canvas and turning them into black ink This will in turn update the spatial queries and generate a new set of results New graphical reasoning models for understanding graphical interfaces is a seminal paper on using graphical rewrite rules for computation Progressively flattening solver results back onto the canvas to create basic 1D cellular automata Recursive rewrites can be used in a lot of interesting ways As an example below is a recreation of a logic gates demo from Inkbase We start by creating the symbols And the rules they follow Which shows us immediate feedback on the canvas We can then set up some logic gate networks and propagate the values through them by writing them onto the canvas to get to the final result A process of propagating values through two logic gate networks Findings We have used Untangle to solve the problems outlined above as we were building the prototype to test our assumptions and intuitions We also conducted several informal interviews with potential users with background in mathematics and logic programming Here are some reflections from that process A smooth ramp from concrete to abstract helps form intuitions about the system Symbols queries and arrows build up on each other Arrows are a reified way of moving a symbol into a box manually Spatial queries are a reified way of selecting things manually Combining the two is a reified way of drawing multiple arrows between multiple symbols “Reification” means giving a concrete representation to an abstract process In this sense each primitive is simply a way of expressing in more general terms what you could already do in an earlier step Gradually climbing this ladder of abstraction helps build intuition about how the system behaves Informal solving is most useful for certain kinds of problems There seem to be two dimensions of complexity for a given problem a problem can have relatively trivial constraints but many elements that need to be solved or can have a small number of elements but constraints that are difficult to satisfy There is a sweet spot where Untangle seems most useful The dataset must be small enough to be manually drawn but with constraints too complex to easily solve in your head If the dataset is large it takes too much effort to write it all down and the tablet screensize limits what can fit on the canvas If the set of constraints is simple enough to keep in your working memory you can often just solve the problem as you create its representation without additional help from the computer We found that the even a small number of overlapping constraints forces us to switch to effortful “System 2” thinking and this is where Untangle shines helping us think through a problem in an informal way Many problem representations look like tables The way we naturally represent assignment problems tends to drift toward using tables Examples of tablelike structures invented adhoc to represent specific problems Even though a structured approach—like a builtin table tool—might seem more appropriate to modeling these kinds of problems freeform input feels important The exact shape of the problem representation might not be clear initially and sketchiness facilitates finding it It feels good to build up to a table rather than being prematurely forced into one Another possibility is that the provided spatial queries column with symbol at top row with symbol at left table lookup etc encourage drawing problems in gridlike structures A rich area for future work would be adding more ways to query the canvas which could lead to more diverse representations Handdrawn input is well aligned with exploratory problemsolving One of our motivations for handdrawn input was to enable drawing symbols and elements that mapped closely to a particular problem domain For example you could draw chairs and tables for a seating arrangement In practice we rarely drew domain objects instead favoring symbols like names logos or even dashes and dots However handdrawn input still felt much more aesthetically fitting than the vector version we tried early on Early iteration of Untangle using vector graphics and artificial symbols At the lab we believe that the fidelity of the tool you use should be proportional to the maturity of the idea you are working on Being forced into crisp vector shapes for exploratory problems creates a cognitive dissonance between the fuzzy nascent problem in our head and the precise symbols on the canvas Fuzziness and live feedback contribute to a conversational feel Untangle was designed to get the user to a result as fast as possible Simply drawing a single arrow can generate multiple results To find a satisfying solution it is often not even necessary to add additional constraints Instead you can just scrub through proposed solutions to find one that makes sense If you find a satisfying solution you can simply stop working even if the results are underspecified In a similar vein if the solver cannot satisfy your constraints rather than showing an error message the system will attempt to ignore some constraints relaxing the problem statement to generate a technically incorrect solution The interface will highlight the arrows that were ignored to generate each solution In realworld contexts we often are not trying to find the globally optimal solution but rather just any reasonable one Spatial queries are also fuzzy We do not look for something “exactly 137px to the left” but “roughly to the left” This plays well with handdrawn aesthetics as you never create perfect sketches Additionally spatial queries highlight their matches directly on the canvas This has two advantages first it helps explain what the query is doing—even if you have no idea of the underlying formalism you can experimentally find out what is happening Secondly it makes it transparent when the imperfect matching algorithm does not work as expected You can always just wiggle your drawing a bit to get the system to recognize it Finally arrows point to and inside of queries rather than of connecting to ports This has a specific informal feel which meshes well with the fuzziness of other parts of the system and is distinctively different from the feel of things snapping into each other Shortcomings The system lacks clear semantics Untangle’s “language” is unspecified and not very composable The set of provided spatial queries is adhoc We created new queries for problems we were solving in the examples instead of building them up from first principles As a result we can solve the examples nicely queries are not composable or abstractable—you cannot combine to the left and to the top to create the lookup query used in the coffee shop schedule nor can you push the results from one query into another one to create reusable functionalities Additionally creating these queries purely by example can be quite tedious—especially when it comes to selecting wildcard configurations It seems clear it would be better to create a match by example then interactively refine it through direct manipulation One exciting piece of research in this direction is described in Perceptual Grouping Selection Assistance for Digital Sketching by David Lindlbauer et al Most importantly it is hard to intuit how the primitives behave beyond basic demos For example there is a subtle difference between constraining elements of the solution space and constraining elements of the match Careful thought is required to discern the difference Turning ink into symbols is an unnecessary technical crutch Untangle is a system for assigning candidate symbols to potential targets In our experience these symbols often consisted of many ink strokes such as for people’s names In order to assign these to a target we need to recognize those strokes as being part of a grouping Using a magic wand to group multiple strokes into a single symbol In past research we found that it was very difficult to reliably and unambiguously group ink strokes or to recognize repetitions For this project we simply sidestepped the problem with a command to create a symbol out of a group of strokes This was convenient for a research prototype but we feel this is unfortunate technical ceremony Similarly when creating a drawing we encourage users to reuse copies of the same target symbol to hint the solver system that those targets are related Sometimes copying objects can be a fast and intuitive thing to do Other times—especially when the shapes are simple—it feels more natural just to draw them again and have them match automatically The history of inferring specific user intent from ink gestures remains an open problem after many years of related work including work on shape recognition for drawing programs and back to early stylusbased text input systems such as Palm’s Graffiti Some parts of the system lack visibility A computing system should never leave a user feeling uncertain about whether the intent of the user has been understood In Untangle assignment arrows are freeform they can exist with or without valid sources and targets This meshes well with the fuzzy aesthetic but our implementation does not provide user feedback whether the arrow has actually connected the items on the canvas other than the updated solutions For this specific example it is easy to imagine how to improve this For example by color coding arrows and connected spatial queries the same way we do for query matches However color coding query components as well as their matches creased a visually noisy rainbow canvas Finding the right queues and feedback for a system like this is a subtle task There is a fundamental tension between maintaining a focus on the user’s input by avoiding unnecessary UI chrome and preventing confusion by providing sufficient feedback Responses from the computer are underdesigned In systems where users and computers collaborate it helps to distinguish between user input and computed responses In Untangle user input is always black and we use pink to distinguish computed results from userdrawn strokes We refer to this as the user voice vs the computer voice Throughout our research we often want the machine to respond and draw with us but what is the “correct” way to do so Because Untangle limits user input to a single color rendering results in pink makes the distinction immediately clear but we worry this would become problematic in a more fullfledged system We briefly explored rendering computed results using a different “pen” for example a stylized marker but that felt uncanny—the user’s input strokes redrawn exactly but with a different aesthetic Small canvas artificially constrains the problem representation In Untangle the relatively small screen size and lack of support for canvas features such as panning or zooming limits the amount of data and the complexity of the problems you can represent Drawing everything by hand also contributes to this limitation—it simply requires too much effort to draw hundreds of student names or create a staff calendar for an entire year We are interested in how the experience of Untangle would evolve as we explored larger scale problems or more complicated representations For example one future project we would love to see is “Untangle with external data” There is no way to explore the solution space One omission in this work is the limited ability to visualize the solution space Yes we can narrow down the solution space by reifying a result “Sam has to review Steve’s paper” or by adding constraints “the wildcard cannot be the same as the contents of the box next to it” but while Untangle allows you to “scrub” through results it only ever shows one result at a time In fact the solution space is not a homogeneous list there are recurring patterns It would be interesting to explore visualizations that revealed clusters or branches of candidate solutions that share similarities or how how different constraints “cut off” certain areas of the solution space Conclusions With this project we set out to discover what a nonbureaucratic theorem prover might look like The traditional programming interface to a theorem prover is both strict and formal Untangle shows a glimpse of a computational model with fuzziness at its core Being able to handwave at a problem and get to results—often on the first browse through the solution space—feels wonderful and is a stark contrast Spatial queries provide a way to create structure on top of a freeform drawing Instead of forcing problems prematurely into tabular form you can start sketching the problem however feels natural You then work with the system to query that diagram for a satisfying solution In some cases the final result may take the form of more traditional tabular data but we found that building up to it from a freeform drawing and not being constrained by it prematurely allowed us to explore our ideas more naturally The combination of symbols spatial queries and arrows provides a nice onramp for abstracting logic Rules can be built up out of simple examples gradually adding assignment arrows or replacing those arrows’ concrete sources and targets with spatial queries We feel this conceptual buildup is very promising and points at a possible way of solving the repetition problem described in the Crosscut essay Untangle is part of our “programmable ink” track of research continuing from previous projects Inkbase and Crosscut We remain optimistic about systems in which you directly manipulate the representation of the problem at hand and that remain alive and reactive This combination allows you to improvise and rely on intuitions instead of having to switch your thinking mode to one of effortful logical computation We see here an exciting glimpse of conversation with a dynamic medium—sketching at the speed of thought and collaborating with the machine We welcome your feedback inkandswitch or helloinkandswitchcom Thank you to everyone who offered feedback and guidance throughout the project Peter van Hardenberg James Lindenbaum Todd Matthews Kevin Lynagh Geoffrey Litt Scott Jenson Joshua Horowitz Patrick Dubroy William Taysom Daniel Krasner Ivan Reese Paul Shen Max Schoening, Harnessing the Medici Effect for More Profound Web3 Impact CARBON Copy Front PageFeatures ReFi Data ProjectsBuildersTokensLandscapeImpact DashboardOpportunitiesKnowledge Content NewslettersThe ReFi WeeklyLearnWeb3 Fundraising Guide for Nigerian NGOs Resources OnChain Grant DirectoryGitcoin Grants CanvasThe Regen AtlasThe Climate Capital StackCCN Metrics GardenX List of ReFi ProjectsAboutSubmit News OpinionHarnessing the Medici Effect for More Profound Web3 ImpactHow we have strayed off the path of originality and how to get back on itBy Trinity Morphy May 21st 2024In this piece Trinity Morphy takes inspiration from a recent event to look at why originality has been so difficult to attain in the Web3 impact space and how a phenomenon called the Medici Effect can get us back on trackI had the privilege of attending a Green Pill Nigeria Impact Tour event two weeks ago In his talk Izzy the lead at Green Pill Nigeria pointed out the troubling trend of imitation in the impact space Each cycle he said seems to be filled with recycled project ideas It has become customary for Project XYZ to emerge with a seemingly novel concept only to be quickly followed by Project ABC essentially a copycat with a new bell or whistleThis lack of originality especially in Web3 impact is not just a hurdle its a roadblock For instance other effective ways exist to utilise impact NFTs apart from sequestering carbon or planting new trees Yet we keep seeing new projects based on the same idea but with a more exciting descriptionHow can we actively encourage a shift from simple recycling to genuine originality The Medici Effect that the most innovative ideas happen when you combine concepts from different fields offers insight By looking beyond the impact field we can unlock the potential for more impactful solutionsWhy we recycle ideas and why originality is so importantpictwittercomsRtpkwgMGk— OwockiΞth owocki May 17 2024Reduced risk and familiarity Humans naturally gravitate towards familiarity Replicating a successful project offers security by minimising the uncertainty of venturing into something completely new Its like following a wellworn path instead of forging one through the wildernessAccess to funding Investors and funding institutions are more likely to back sectors with a proven track record of projects A copycat project can point to the success of the original and argue that it can replicate that success with its own twistBandwagon effect When a project becomes popular others aim to capitalise on the hype and user base On the surface launching a copycat project appears easier as does the marketing that goes with itAvoiding mistakes A successful project has already learned what works and what does not Emulation enables new projects to sidestep those pitfalls and concentrate on innovationOriginality is crucial to tackling our social and ecological problems It allows us to see things differently question assumptions and uncover new possibilities This fresh perspective can lead to new solutions we would not have considered otherwise It empowers us to challenge outdated or dysfunctional systems and propose solutions that address their shortcomings from the ground up Original thinking enables us to recognise the potential in underutilised resources and address problems at their roots not simply treat their symptomsEasier said than done of course We need to look to the Medici Effect for a roadmapThe Medici Effect and Web3 impactThe Medici Effect states that the most original and extraordinary ideas occur when you combine concepts from different fields disciplines or cultures It was discovered by Frans Johansson and shared in a book of the same name A majority of the ideas in this section are borrowed from the book and modified to fit Web3 impactSome examples of great products that have stemmed from the Medici Effect include Silvi reforestation Web3 M3tering Protocol renewable energy distribution Web3 Gitcoin fundraising Web3 and Toucan Protocol voluntary carbon markets Web3Heres how we can get better at using the Medici Effect to our advantageDismantle the barrier between Web3 and other fieldsFirst we must be willing to break the associative barriers that exist between Web3 and other fields How do we do this Through exposure to a diverse set of cultures Culture in this context extends beyond geographic boundaries to encompass ethnic class professional and organisational differences By immersing ourselves in these diverse backgrounds we can unlock a more open and questioning mindset and challenge our assumptionsWe also need to embrace broad selfeducation Traditional education often compartmentalises knowledge but selfdirected exploration across disciplines expands what is possible Without it our thinking is limited and we inadvertently stifle creativity Selfeducation empowers us to discover unexpected connections and envision how concepts in other fields can combine to create groundbreaking Web3 impact solutionsCombine random conceptsIntersectional ideas are groundbreaking because the concepts involved are so different and the combinations so unusual that no one would have thought them possible Take the inspiration for this article as an example It happened after I came across an X account named Cozomo de Medici I was not thinking about Web3 impact or the Medici Effect That Is how random combinations work You have no control over it It just comes Rather than leaving luck to do the work we can continuously stimulate our brains to keep producing these random combinations How do we achieve thisNurturing our curiosity By obsessing over new ideas approaches and perspectives we enhance our brains ability to blend random concepts In the foreword of Exploring MycoFi Scott Morris pointed to Emmett Jeffs relentless fascination with mushrooms and mycelial networks and how it led to the creation of MycoFi a novel cryptoeconomic model inspired by the structure of mycelial networksInteracting with diverse groups of people Engage a diverse group of people and we will be presented with a diverse set of perspectives Interacting with such groups can spark unexpected connections For example a conversation between a Web3 enthusiast and a custodian of tradition might lead to an idea to preserve cultural heritage using blockchainThese are what create the conditions for the next phaseIgnite and evaluate an explosion of ideasThe strongest correlation between quality and quantity of ideas is in fact the number of ideas Do you know how many ideas you can get by simply combining concepts from environmental science with Web3 concepts A LOT That is why it irks me when I see so many projects centering on carbon credit tokenisation when there are so many ideas yet to be explored The question here is once these ideas start flooding in how do we handle themFirstly capture as many ideas as we can Keep track of all the ideas our brains generate and set a target to reach before evaluating their feasibility Secondly we need to take our time evaluating because our minds will quickly judge the value of an idea by comparing it to what is already known to work Its important that we evaluate each idea as sincerely as the next whether its gamifying traditional classroom learning or eradicating open defecation in underserved communitiesComing up with great ideas does not guarantee innovation however We must make those ideas happenMake intersectional ideas happenThe paradox of innovation at the intersection of fields is rooted in the symbiotic relationship between ideas and failures the more ideas we explore the higher the rate of failure Far from being a negative consequence failures are a vital part of the innovation journey We learn and grow through them so that we can do better the next time Not acting for fear of failure robs us of this crucial phaseDaring to try ideas opens us to a world of invaluable insights that help us refine our approach identify weaknesses and ultimately discover the path to a truly groundbreaking solution In my interview with Christwin of Switch Electric and M3tering Protocol he shared a fascinating story about the early days of his solution The first model they tried unexpectedly incentivised the consumer to overload the solar infrastructure leading to severe component wear and tear and attracting steep maintenance costs This was a significant failure but it led to research that brought about the idea of building M3tering Protocol on blockchain to track consumption and ensure transparencySince failures are inevitable we can allocate specific resources for testing each new idea and minimising the potential for catastrophic failure This allows for rapid iteration where we can learn from each attempt refine our approach and move on to the next experiment with valuable insights Do Not forget to document everything along the way and share the results within the team This knowledge base becomes a valuable resource for future projects because it prevents the same mistakes and accelerates future breakthroughs We saw this in the transition from Gitcoin 10 and Gitcoin 20We also need to stay motivated along the way because the path to ingenuity is rarely linear There will be setbacks and failures that make us question our actions Staying motivated requires keeping the longterm vision in mind and focusing on the positive impact our work can bring to the world We need to celebrate all wins big and small whether its successfully completing a pilot project achieving a user engagement milestone or receiving positive feedback from a target community This reinforces our belief and helps us pushing forward despite the inevitable setbacksConclusionThe Web3 impact space has potential to change the way we tackle the worlds most pressing challenges Were not getting there however if we keep recycling the same old ideas Originality is the key if we are to truly unleash Web3 impact We must look beyond our own siloes break down barriers and ignite curiosity across a variety of fields to spark the kind of breakthrough ideas that will move the needleAnd when those ideas do come we must not shy away from failure and its valuable lessons Nature exemplifies this beautifully a butterflys struggle to escape its chrysalis is anything but pleasant Still this phase is necessary for the butterfly to strengthen its muscles expand its wings and ultimately fly Embrace the journey celebrate even the smallest wins and surround yourself with a supportive network Together we can embrace the power of the Medici Effect to create a better future for ourselves and the planetThis article represents the opinion of the authors and does not necessarily reflect the editorial stance of CARBON CopyCopyright © 2025 CARBON CopyToken data provided by CoinGeckoFront PageFeaturesLearnReFi ProjectsAboutSubmit News, 5 DeSci projects disrupting scientific research and development — Crypto Altruism 0 Skip to Content BLOG CATEGORIES DAOs EDUCATION ENVIRONMENT REFI EQUITY INCLUSION FINANCIAL INCLUSION DEFI NFTs PHILANTHROPY SCIENCE DESCI SOCIAL IMPACT SUPPLY CHAIN COMMENTARY PODCASTS CRYPTO ALTRUISM PODCAST THE WEB3 NONPROFIT IMPACT ON OPTIMISM INFOGRAPHICS RESOURCES BECOME A CRYPTO CHARITY DONATING CRYPTO LEVERAGING AI AT YOUR NONPROFIT ABOUT US WHO WE ARE TRANSPARENCY AFFILIATE PARTNERSHIPS CONTACT SUPPORT US Open Menu Close Menu Open Menu Close Menu BLOG CATEGORIES DAOs EDUCATION ENVIRONMENT REFI EQUITY INCLUSION FINANCIAL INCLUSION DEFI NFTs PHILANTHROPY SCIENCE DESCI SOCIAL IMPACT SUPPLY CHAIN COMMENTARY PODCASTS CRYPTO ALTRUISM PODCAST THE WEB3 NONPROFIT IMPACT ON OPTIMISM INFOGRAPHICS RESOURCES BECOME A CRYPTO CHARITY DONATING CRYPTO LEVERAGING AI AT YOUR NONPROFIT ABOUT US WHO WE ARE TRANSPARENCY AFFILIATE PARTNERSHIPS CONTACT SUPPORT US BLOG Folder CATEGORIES Back DAOs EDUCATION ENVIRONMENT REFI EQUITY INCLUSION FINANCIAL INCLUSION DEFI NFTs PHILANTHROPY SCIENCE DESCI SOCIAL IMPACT SUPPLY CHAIN COMMENTARY Folder PODCASTS Back CRYPTO ALTRUISM PODCAST THE WEB3 NONPROFIT IMPACT ON OPTIMISM INFOGRAPHICS Folder RESOURCES Back BECOME A CRYPTO CHARITY DONATING CRYPTO LEVERAGING AI AT YOUR NONPROFIT Folder ABOUT US Back WHO WE ARE TRANSPARENCY AFFILIATE PARTNERSHIPS CONTACT SUPPORT US 5 DeSci projects disrupting scientific research and development Project HighlightsScienceDAOs Mar 30 Written By Drew Simon 2021 was the year of decentralization and this momentum has only increased into 2022 Not only have we seen incredible growth in the decentralized finance DeFi space but we have also seen the emergence of social impact DAOs decentralized media platforms decentralized VC funds and more recently the emergence of a new field – Decentralized Science or DeSci In short “the decentralized science DeSci movement aims to harness new technologies such as blockchain and ‘Web3’ to address some important research pain points silos and bottlenecks” Whereas scientific research has long been viewed as overly bureaucratic and disjointed the DeSci movement aims to improve this by using blockchain to offer greater transparency and to take on the “profit hungry intermediaries” such as scientific journals that have dominated the traditional research spaceFor some resources on DeSci I recommend you check out the following articlesDeSci an opportunity to decentralize scientific research and publicationA Guide to DeSci the Latest Web3 MovementCall to join the decentralized science movementFor this blog post we will be highlighting 5 DeSci projects that are leading the way and positively disrupting scientific research and development1 VitaDAOOne of the best examples of DeSci in action is VitaDAO a Decentralized Autonomous Organization DAO focused on funding longevity research in “an open and democratic manner” Specifically they are focused on the decentralization of drug development focused on the extension of human life and healthspan They fund earlystage research with the goal of turning the research into biotech companiesVitaDAO is government by holders of VITA tokens which can either be purchased or earned through contributions of work or intellectual property With over 4000 members and 9M in funding raised to support scientific research VitaDAO has proven that the DeSci movement is no laughing matterCheck out some of their featured projects here2 SCINETThe SCINET platform which is built on blockchain enables retail and institutional investors to securely invest in scientific research and technology directly In addition to funding promising scientific research they also offer a “blockchainpowered” cloud laboratory for researchers a rigorous decentralized peer review process and enable researches to document their IP on an immutable blockchain3 AntidoteDAOAntidoteDAO is a decentralized community focused on funding cancer research and other cancer initiatives Their ecosystem includes a governance token and NFT collection which both enable individuals to vote on where to allocate funds In addition to providing funding to charities supporting cancer research and cancer patients a core focus of the DAO is on providing 100K seed fund grants to cancer research teams Research projects are first reviewed by the DAO’s Medical Advisory team and then put to the community for a vote Fun fact we have an upcoming podcast episode with AntidoteDAO that when available will be published HERE Crypto Altruism uses Ledger to keep its assets safeYou’ve probably heard the phrase “not your keys not your coins” By choosing a hard wallet like the Nano S Plus to store your crypto you can rest assured that the keys and the crypto are truly yoursGet your Ledger Nano S Plus now by clicking HERE or on the image below 4 LabDAOLabDAO is an emerging organization which is dedicated to operating a communityrun network of wet and dry labs with the goal of advancing scientific research and development A wet lab is one focused on analysing drugs chemicals and other biological matter whereas a dry lab is one focused on applied or computational mathematical analysis LabDAO is a relatively new project that is still in its infancy but has a promising mission and strong community of support around it 5 MoleculeMolecule is a decentralized scientific research funding platform that operates as a marketplace for researchers seeking out funding and individuals looking to invest in scientific research projects They are “connecting leading researchers to funding by turning intellectual property and its development into a liquid and easily investable asset”Researchers can list their research projects on the Molecule marketplace as a means to engage with potential investors and to secure funding for their project Molecule currently has over 250 research projects listed on their marketplace over 4500 DAO community members and 3 “Bio DAOs” with over 10M in funding in their network According to Molecule “The future of life science research will be driven by open liquid markets for intellectual property powered by web3 technology”We cover more amazing DeSci projects in our more recent postTen more DeSci projects disrupting scientific research development and knowledge sharing Buy me a coffee Send a tip in ETH cryptoaltruismethLike what you are reading Consider contributing to Crypto Altruism so we can continue putting out great content that shines a light on the good being done in the crypto and blockchain community SUPPORT CRYPTO ALTRUISM Please note we make use of affiliate marketing to provide readers with referrals to high quality and relevant products and services DeScidecentralizationscienceblockchainlists Drew Simon Previous Previous Crypto Altruism Podcast Episode 39 AntidoteDAO Decentralized funding of cancer research and charitable initiatives Next Next Crypto Altruism Podcast Episode 38 Using NFTs to empower content creators and help kids learn ft Susie Jaramillo CONTENTBLOGPODCASTINFOGRAPHICSCURATED LISTS ABOUTABOUTSUPPORT USCONTACTDISCLAIMERPRIVACY POLICY Buy me a coffee ETHERC20 cryptoaltruismeth 0xac5C0105914F3afb363699996C9914f193aeDD4A Sign up for our monthly newsletter Thank you © Crypto Altruism 2023 FOLLOW, A Short History of BiDirectional Links Home The Garden Essays Notes Patterns Smidgeons Talks Podcasts Library Antilibrary Now About The Garden Essays Notes Patterns Smidgeons Talks Podcasts Library Now About Essays evergreen A Short History of BiDirectional Links Seventy years ago we dreamed up links that would allow us to create twoway contextual conversations Why do not we use them on the web Design Digital Gardening The Web Web Development Planted almost 5 years ago Last tended about 4 years ago Table of Contents Bidirectional links are not new Bidirection Linking in Personal Digital Gardens Building Your Own BiDirectionals BiDirectional Linking with WebMentions Table of Contents Bidirectional links are not new Bidirection Linking in Personal Digital Gardens Building Your Own BiDirectionals BiDirectional Linking with WebMentions With the recent rise of Roam Research the idea of bidirectional linking is having a bit of a moment We are all very used to the monodirectional link the World Wide Web is built around They act as oneway pointers we follow in a linear sequence While we can link to any site the destination page has not a clue we have done so We set up all these singledirection paths trying to signal relevance and context only to have the other side completely ignore our efforts Our monolinks are trying to establish relationships in vain We are starting to look around our monolinked environment and wonder why it is so hard to surface relevant contextual relationships Manually interlinking content takes an awful lot of human curation and effort Efforts we should probably slog off onto our systems Enter the bidirectional link A bidirectional link has social awareness it knows about other pages or ‘nodes’ that point to it and can make them visible to people This means we get a twoway conversation flowing between our web locations Bidirectional links are not new The idea of the bidirectional link goes back to 194580ya when Vannevar Bush dreamed up the Memex machine Vannevar outlined this hypothetical gadget in an essay in The Atlantic called As We May Think He wanted a system capable of “associative indexing… whereby any item may be caused at will to select immediately and automatically another… so that numerous items have been thus joined together to form a trail” This essay turned out to be a foundational document for the ideologies that directly led to both the internet and the Web Yes those are two entirely separate pieces of technology Vannevar was one of the key movers and shakers rallying folks to help build the original internet infrastructure He corraled folks at MIT the US Department of Defence the National Science Foundation and various research labs like the Standford Lincoln Lab Bell Labs the RAND Corporation and Xerox PARC to get involved Walter Isaacson The Innovators How a Group of Hackers Geniuses and Geeks Created the Digital Revolution London Simon Schuster 201510ya Suffice to say the guy was driven by a belief that enabling people to connect information and share knowledge would expand the scope of human understanding The Memex was one idea of how that might manifest in material form Vannevar even created a small informative diagram of this deskbound vision Marketing chops 101 Vannevar’s evocative description of the Memex is especially impressive given that digital computers had only come into existence 5 years earlier Most were still the domain of large military operations like Bletchley Park and were seen as inconveniently large calculators Implementing a wildly interactive computational personal knowledge base was not much of an option So the idea went into hiberation and did not resurface until the idea of personal computing began blooming in the sixties and seventies Ted Nelson an unlikely film director and sociologist stumbled into a series of computing lectures and began to imagine how graphical interfaces might reinvent the way we write and connect ideas He took inspiration directly from Vannevar’s essay and in 196560ya when he coined the term hypertext to describe his vision for a sprawling network of interlinking information Nelson planned to implement these hypertextual dreams in his perpetuallyimminent Project Xanadu If you have some time this is quite the internet history rabbit hole to run down Ted Nelson is on another level The Xanadu project was a hypertext system that imagined that every sentence block and page would be part of a vast bidirectionally linked network A design mockup of how Project Xanadu might visually connect pieces of text across multiple documents You would be able to trace information back to its origin the way current web links do But you would also be able to see who had referenced remixed and expanded off that original The full Pattern Language of Project Xanadu expands far beyond just bidirectional links to include features like Transclusions but we will not dive into it all here Suffice it to say Xanadu did not pan out Instead we got the less fancy but far more real and useable World Wide Web that currently does not support bidirectionals on an infrastructure level While Sir Tim Berner’s Lee wrote himself a note debating their pros and cons back in 199926ya there is an obvious design issue with letting twoway connections flow freely around the web If every site that linked to yours was visible on your page and you had no control over who could and could not link to you it is not hard to imagine the Trollish implications… Figuring out how we might filter moderate and set permissions around link visibility turned into quite the challenge The design details grew complex It became clear implementing the Web with simpler monodirectional links was the right thing to do given that its creators wanted universal adoption Lots of people are still mad about it Let us not venture too far down that historical wormhole The TLDR is technology is hard Until Xanadu ships and we are all immersed in the universe of multilinked versioncontrolled nodes of remixable microcontent that somehow solves the problems of permissions and moderation there are still plenty of ways we can resurrect the possibility of bidirectional links on the web Bidirection Linking in Personal Digital Gardens Most of the design issues with adding bidirectional links to the global web were related to moderation and permissions However adding them within the bounds of a single website with one author sidesteps that problem There is been a flurry of interest around bidirectionals among people involved in the Digital Gardening movement Much of this was originally sparked by Andy Matuschak’s notes Go have a good browse through them Andys linked notes stack on top of one another allowing you to browse to new notes while previous notes are still visible There is plenty to admire here It should be noted Andy is an experienced developer and interaction designer and these notes should not be taken as the standard expectation for the rest of us normal plebby internet citizens But the key part of this system that creates interlinked context is the “Links to this Note” section at the bottom of each post Anytime Andy links to another one of their notes on the site it will pop up as a related note at the bottom of the page This is the bidirectional dream It gives us a way to navigate through these ideas in exploratory mode rather than navigating a hierarchy of categories on a main index page Since it is all contained within a singleauthor site our SpammishTrollrisk factor is at a comfortable zero This is mildly tangential but I love how the topic of bidirectional links makes fully visible our “websites are locations” and “websites are containers” conceptual metaphors with “inside” and “outside” links Building Your Own BiDirectionals That is all very cool but how are you supposed to build bidirectionals into your own site Thankfully setting up your own public gardening bidirectional Memex does not involve Xanadu One fantastic option for nondevelopers is based around a personal wiki system called TiddlyWiki AnneLaure Le Cunff wrote up an easytofollow guide to getting your own up and running For those of us here for the hypercustomised overengineered JavaScript solution that would be me the Gatsbyjs community has a number of active gardening enthusiasts building themes and plugins I built mine using Aengus McMillin’s gatsbythemebrain Aengus has documented the theme well and it is not too challenging to implement as long as you are comfortable in JavaScript and React I also curate a list of tools for Digital Gardening on this Github repo BiDirectional Linking with WebMentions While I argued that Webwide bidirectional links are unlikely to happen at a global scale there is a way you can add bidirectionals to your personal website that picks up on references anywhere on the web WebMentions are a piece of web infrastructure the IndieWeb community has done a lot of work to advocate for The W3C gave the specification recommendation status in 20178ya The system notifies a URL whenever that site is mentioned elsewhere on the web You are then able to show that mention and its contents on your site It is essentially an optin bidirectional linking system Plenty of folks have written useful guides on how to add these to your site Here is one for any static site one for Gatsby one for Nextjs There is a whole list of implementation examples on the IndieWeb Wiki you can look through 5 Backlinks A Brief History Ethos of the Digital Garden A newly revived philosophy for publishing personal knowledge on the web Digital Gardening for NonTechnical Folks How to build a digital garden without touching code Transclusion and Transcopyright Dreams The lost permissioning and copyright system of the Web The Pattern Language of Project Xanadu Project Xanadu as a pattern language rather than a failed software project A MetaTour of This Site A video tour through how I build the old version of this site Mentions around the webCarlos Sanmartín Bustosmentioned in En busca de enlaces bidireccionalesJune 24 2024Una de las cosas que echo en falta al haber pasado el blog a un sitio estático son los links bidireccionales No tanto los links que provengan de fuera que hoy en día van a ser mínimos como los links internos que permiten explorar el blog por ejemplo para avanzar hacia el futurAngsuman Chakrabortymentioned January 07 2023A Short History of BiDirectional Links CypherNewsmentioned January 04 2023 Hacker News A short history of bidirectional links 2020 hackernews HN Front Pagementioned January 04 2023A Short History of BiDirectional Links L C newsycombinatorcomitemid342447…Winson Tangmentioned January 04 2023A short history of bidirectional links 2020 Hacker Newsmentioned January 04 2023A short history of bidirectional links 2020 Patrick Durusau ⏳ White Person on White Supremacymentioned May 18 2022codexeditor I Have lost the tweet where I saw this mentioned earlier today I like the Web Mentions idea esp if we could use XPath to point to less than the page level Thoughts Show 3 more Want to stay up to date Subscribe via RSS Feed © 2025 Maggie Appleton The Garden Essays About Notes Now Patterns Podcasts Talks Smidgeons Colophon Library, Part 1 Introduction to Responsible Technology by goodbot MediumOpen in appSign upSign inWriteSign upSign inPart 1 Introduction to Responsible TechnologygoodbotFollow11 min read·Aug 3 2023ListenShareIntroductionIn late 2022 the GoodBot team — consisting of a group of sociallyminded professionals working in law technology and policy — came together to develop a snapshot of Canada’s current Responsible Technology landscape This is a space that to date had been heavily defined by voices from the United States Our goal is to understand the Canadian ecosystem’s current composition capacity and direction particularly how technology impacts Canadians what issues are of focus in research and programming and how the policy landscape is evolving at the provincial national and international levelsTechnology is revolutionizing everything from healthcare to education to law to climate science and government but is also associated with a wide range of risks and harms making responsible technology governance a critical priority for governments nonprofits and marketsNew visions clear policy frameworks effective implementation methods and multistakeholder oversight bodies are needed to navigate this landscape It also requires public interestfocused strategic collaboration that includeslongterm research on harmsmore transparency and collaborative efforts with technology companies to strengthen safetyeffective mechanisms to hold companies accountable when they fail to act in response to harminvestment in public interest technology and philosophies that prioritize healthy technology ecosystemsunderstanding the leverage points and incentive systems that contribute to these outcomes andthe development of the critical capacities needed to meet this momentWe know from the last two decades that when technology tools and platforms become deeply embedded in institutions like media and education before they are regulated they become harder to govern This reality has led to escalating and lasting harm in a number of areas The pressing question now is how to forge a new direction recognizing the immediate need to take actionThis is the introduction to a research project on Canada’s Responsible Technology landscape GoodBot’s goal with this research is threefoldTo understand the current landscape and priorities of Canada’s Responsible Technology ecosystem including the who what where and howTo highlight gaps and opportunities within this ecosystem that can help Canada develop a more robust impactful and collaborative approach and agenda andTo understand what role GoodBot can play in advancing Responsible Technology at home and around the worldWhat is Responsible TechnologyResponsible Technology acts as an umbrella for a range of approaches and terms that all focus on different issues or specific intervention points in technology and business life cycles It includes concepts such as ethical tech humane tech tech stewardship and public interest tech all of which are connected and overlap but which also center on different locus of influence These and other terms will be explored in Part 1 of our seriesResponsible Technology is a relatively new framing that includes a wide range of issues related to technology Some issues — like privacy and freedom of expression — are longstanding cornerstones of the most established technology nonprofits in the country while conversations on Generative AI risks are relatively new Yet technology and AI ethics have been around for decades with themes prominent among academic labs human rights defenders peacebuilders and in other convening spaces What has changed is the scale and pace of technology and the amplification of new risks and narratives surrounding technology harms These have created a growing awareness of the need for safetyfocused design and research at the outset meaningful oversight of technology companies and effective accountability mechanisms when companies fail to act in the public interestMany technology tools and businesses currently fail to meet even a vague understanding of Responsible Technology This is especially true for small to medium technology companies who focus on survival and leave proactive assessment and harm mitigation as an afterthought if they get any attention at all Others have social impact strategies that are completely detached from their business modelFew companies start with the goal of causing harm but unintended consequences can arise due to a lack of intentional consideration capacity and unanticipated and conflicting priorities Additionally as products scale seemingly harmless matters can lead to real harm as user bases grow use cases expand and incentive structures change The explosive emergence of generative AI has made it even more clear that left unaddressed these structural factors risk widening the gap between privatized profit and socialized riskIn spite of these growing concerns several Big Tech companies have chosen to lay off large segments of their Trust and Safety teams seeing them as cost centers that add undesirable operational complexity Even when companies have Trust and Safety teams in place they are often pitted against product teams The result is companies that increasingly seek to automate these decisions which frequently and disproportionately impact minority communities including human rights defendersSome companies have begun sharing Transparency Reports which is a move in the right direction However there are no agreed standards or metrics against which to assess companies’ commitment to social sustainability nor is there any external oversight These factors lead to the possibility of ‘tech washing’ and cherrypicking data that provide the appearance of taking action but in ways that lack substantive effect or because new harmMoreover even companies that have the desire to act responsibly can lose sight of their original goals when they face demands for outsized returns from investors — including venture capitalists and private equity investors — which can place them at odds with decisions that are in the public interestIn this context a wide range of social harms and externalities have arisen — many of which are unintentional — and which includeBiased Unaccountable Untransparent AutomationBias in untransparent algorithms that discriminate against marginalized groupsDisruption of the workforce by generative AI in almost all professional sectorsBig Tech DominationBig Tech market domination to control value chains through predatory pricing terms and acquisitionsNonconsensual selling of personal data to and from thirdparty data brokersAddiction Mental HealthThe use of dark patterns to drive engagement and addiction in gaming and social mediaThe decline of attention spans at a population level in the last 20 yearsThe decline in mental health and body image especially among youth leading to self harm and deathHarassment Violence ExtremismIncitement to radicalization extremism and even genocideTrolling doxing and harassment including targeting women trans and BIPOC peopleBad ActorsTargeted and opportunistic disinformation and microtargeting to undermine democraciesScams to steal millions from people through generative AI or with crypto hacksTrafficking of women and girls on the dark web and in mainstream platformsThis is by no means a comprehensive list In response Responsible Technology advocates have advanced efforts in recent years to understand the wide array of externalities impacting different levels of society These initiatives variously aim to understand harms and causes increase public awareness and engagement incentivize governments to enact new laws and enforce existing ones and create solutions that lead to safer and more responsible technologyenabled environmentsAdditionally a new wave of government and nonprofit investigations and litigation aims to clarify technology companies’ responsibilities and identify leverage points to incentivize responsibility These efforts have had some successes but are often too incremental and underresourced to keep paceThe scale and complexity of issues arising from technology are unprecedented Canada needs a clear Responsible Technology agenda and sufficient investment to move toward a technological future defined by healthy people businesses markets societies and democraciesThe Asymmetry Sustainability GapA key barrier facing Responsible Technology advocates — including journalists academics tech nonprofits technologists tech ethics experts policymakers and citizens — in addressing technology harms is an existing and growing set of asymmetrical disadvantages when compared to the companies and sectors responsible for harmThese disadvantages manifest in many forms including limited access to talent data sets algorithms infrastructure information internal research and audits knowledge and resources It shows up in access to capital restrictions on how capital can be used and comparatively robust ethical requirements It is further exacerbated by companies’ anticompetition tactics to buy out underprice feature bundle and otherwise aggressively quash any disruptors who may be able to offer healthier alternativesAdditionally asymmetries show up when comparing the inputs and outcomes around harm It is — for example — much less resource intensive to create campaigns to disseminate disinformation on vaccines — than it is to undo the damage caused by this disinformation This reality places a societal premium on considering what effective oversight governance and accountability of technology look like but also raises the need to balance corrective actions with Freedom of Expression FoE norms The global nature of many technology platforms means that US norms are effectively imposed on Canada and other countries Yet Canada has its own unique and wellestablished interpretations of fundamental freedoms that should be considered and protected in the face of technological changeCanada’s Responsible Technology ecosystem is small and underresourced compared to its US counterparts and at this time there are few prominent ecosystemlevel organizations that are wellpositioned to guide a Responsible Technology community and strategy Yet to effectively influence outcomes Responsible Technology advocates need to work together including by establishing new governance innovationsA critical factor in the Canadian context is that much of the funding to date has focused on understanding symptoms and immediate causes rather than underlying structural issues and incentive systems at play Some of this is a product of new and emerging organizations with limited track records while other issues arise from inadequate and restrictive funding and opportunities Some organizations only work on technology matters at a project level rather than a mission level Such factors are important to understanding the limitations on Canada’s capacity and sustainability Our sixth report will explore Canada’s nonprofit capacity in more depthAn additional barrier is that there are no obvious market solutions to address many of the problems that arise from technology For example while technology has led to unprecedented online harassment of women people of color and LGBTQ communities companies offer limited solutions aimed at limiting harassmentThis reality is exacerbated by the fact that markets recently rewarded technology companies for cuts that significantly depleted their Trust Safety teams even when it occurred at a time of high salience around the risks posed by technology platformsLack of coordination is also a factor among tech companies For example some companies argue that if they do not employ harmful tactics such as polarizing content or algorithms to attract attention they will lose out to rivals who will These realities point to an increasing need for sectors to collaborate toward reducing harm and promoting public interestIndeed in areas where companies have invested more material resources — including to address extremism and protect children — even Big Tech lacks the bandwidth to address the complex range of issues on its own making collaboration essential Within the tech sector new multistakeholder initiatives such as Global Internet Forum to Counter Terrorism and the Tech Coalition have been launched in an effort by technology platforms — and include human rights advocates governments and researchers — who work collectively to reduce extremism and child sexual abuse material online respectively Such issues are even more challenging for smaller platforms and startups that lack internal resources to respond to emerging and unanticipated issuesUltimately while technology companies contribute many benefits to society they also contribute significant problems that neither society the markets nor they are presently able to solve They often lack incentives to prevent and address problems up front and even when they want to do the right thing investor incentives can derail their decisions There are limited market incentives to address challenges created by businesses and market competition Moreover our governance institutions operate in ways that are incompatible with the fastmoving pace of technology which presently tend to focus on harm to individuals instead of on harm to society These factors together mean that we are in a situation that is by definition unsustainable We need collective action to address these risks including through responsible resources capacities frameworks budgets and policiesCanada’s Policy LandscapeWhile several technologyfocused bills are in development Canada’s current policy landscape is far behind the advances of the last 20 years This is also true of many other countries that currently lack the policies capacities institutions and enforcement mechanisms needed to govern a rapidly evolving technology environment Furthermore research shows that even where effective policies are in place underresourced enforcement mechanisms such as antitrust hamper the ability of governments to enforce existing laws In this context the role of civil society organizations is particularly importantWhile the policy landscape is expected to evolve rapidly we do not know what effect these policies will have or how coherent they will be across jurisdictions and issues Canada has introduced many bills for consideration but few have passed and all leave much to be desired In the intervening time legal firms and the Privacy Commissioner have advanced litigation — with a particular focus on privacy and antitrust — to hold technology companies accountableCivil society organizations often lack consensus on addressing key issues For instance Online Harms advocates support stricter content moderation to tackle harassment extremism and child exploitation In Canada some lean towards Freedom of Expression while others recognize the need to address such harms but fear that wellintentioned policies could inadvertently suppress the voices of vulnerable communities Balancing these competing rights is complex Responding to emerging issues and harms that affect us all requires better public engagement This includes open and inclusive dialogue transparent consultation processes and effective accountability mechanisms to navigate these complexities and to help uphold and balance a range of fundamental Canadian rightsIndeed there are no ‘right’ answers but rather ‘different tradeoffs’ Moreover there are ways to escape such polarity traps which can easily become politicized resulting in deadlock Even among nonprofit organizations such as the ones that are seemingly at odds on online harms for example both largely agree that passing comprehensive privacy frameworks would mark an important victory and achievementYet even if we achieve effective regulation and enforcement addressing entrenched asymmetries — especially those caused by Big Tech — requires a collective agenda and roadmap What is clear is that our current institutions lack the capacity and resilience needed to address the challenge we faceAs Canadians we have an opportunity to draw upon the values that make us strong as we reimagine our relationship with technology Ideas such as Indigenous approaches to data sovereignty collaboration and multiculturalism have much to teach us about how to navigate these complex issues This moment presents an opportunity to rethink and localize the who how and why of technology governance This is both a daunting and an exciting challengeOpenSourcing GoodBot’s ResearchFor GoodBot our first step is to practice our open principles by sharing what we have learned We hope that this research can lay the groundwork for building a Canadian coalition to support its nascent and necessary Responsible Technology movementGetting to impact requires understanding Canada’s existing capacity understanding the systemic issues at play exploring moral and policy considerations surfacing current and emerging asymmetries of power and exploring how AI is upending companies and industries It also requires a collective strategy and targeted action focused on moving toward responsibilityThese documents are intended to act as a primer for anyone seeking to make an impact in addressing critical priorities facing Canada and the world While our early research may initially be of more value to nonprofits and academics and should be considered a WorkinProgress we aspire to a future where solutionsoriented multistakeholder collaboration is a new norm Our research will be broken into two partsPart 1 is a Canadian Responsible Technology Landscape that explores common terms civil society stakeholders current and emerging policies and litigation and how asymmetries of power manifestPart 2 reviews the results of a survey conducted key observations on the current and emerging landscape and critical reflections on how to strengthen interdisciplinary collaboration among nonprofit organizations academia the tech sector and governmentIn an ideal world this work will lead to highlevel consultations and strategies developed in collaboration with other ecosystem organizations motivated to move this conversation forwardCanada as a Global Leader in Responsible TechDespite and perhaps because of the wide array of challenges Canada has an opportunity to become a global leader in developing deploying and governing technology in socially sustainable ways Getting there requires an urgent focus on strengthening national capabilities by investing in strategic and systemsfocused multistakeholder mechanismsIndeed organized effectively Canadian civil society represents critical and untapped assets to help meet this moment There is also a need to strengthen citizen education advance responsible policy and oversight create technical solutions to advance the public interest introduce responsible technology certifiers and respond to systemic factors that lead to harmful outcomes Canadians can no longer afford to wait The time to engage is nowVersion 10 July 2023 Written by Renee BlackFollowWritten by goodbot3 Followers·1 FollowingFollowNo responses yetHelpStatusAboutCareersPressBlogPrivacyRulesTermsText to speech
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