tag:notes.byed.it,2014:/feedNotes2023-06-27T07:35:51-07:00Nitzan Hermonhttp://notes.byed.itSvbtle.comtag:notes.byed.it,2014:Post/library2023-06-27T07:35:51-07:002023-06-27T07:35:51-07:00AI Library<h2 id="essays_2">Essays <a class="head_anchor" href="#essays_2">#</a>
</h2><h3 id="venture-beat_3">Venture Beat <a class="head_anchor" href="#venture-beat_3">#</a>
</h3>
<ul>
<li>
<a href="https://venturebeat.com/ai/a-sober-view-of-ai-will-lead-to-more-effective-innovation/">A sober view of AI will lead to more effective innovation</a> (2017)</li>
<li>
<a href="https://venturebeat.com/ai/intellect-vs-intelligence-the-difference-matters-in-ai/">Intellect vs. intelligence: The difference matters in AI</a> (2017)</li>
</ul>
<h3 id="creativity-post_3">Creativity Post <a class="head_anchor" href="#creativity-post_3">#</a>
</h3>
<ul>
<li>
<a href="https://www.creativitypost.com/technology/step_0">Step 0</a> (2018)</li>
<li>
<a href="https://www.creativitypost.com/technology/multidimensional_thinking">Multidimensional Thinking</a> (2018)</li>
<li>
<a href="https://www.creativitypost.com/technology/post_taylorist_design">Post Taylorist Design</a> (2018)</li>
<li>
<a href="https://www.creativitypost.com/technology/an_argument_against_agi">An Argument Against AGI</a> (2017)</li>
</ul>
<hr>
<h2 id="talks_2">Talks <a class="head_anchor" href="#talks_2">#</a>
</h2><h3 id="tedx-2016_3">TEDx (2016) <a class="head_anchor" href="#tedx-2016_3">#</a>
</h3>
<iframe width="560" height="315" src="https://www.youtube.com/embed/F0BbZRr8jbk" title="YouTube video player"></iframe>
<h3 id="aia-2018_3">AIA (2018) <a class="head_anchor" href="#aia-2018_3">#</a>
</h3>
<iframe src="https://player.vimeo.com/video/382607254?h=6472104b8c" width="640" height="360"></iframe>
<h3 id="dif-2017_3">DIF (2017) <a class="head_anchor" href="#dif-2017_3">#</a>
</h3>
<iframe width="560" height="315" src="https://www.youtube.com/embed/AsB4-mCICM0" title="YouTube video player"></iframe>
<h3 id="google-2016_3">Google (2016) <a class="head_anchor" href="#google-2016_3">#</a>
</h3>
<p><a href="https://docs.google.com/presentation/d/1sIh35jGEZThiuH06IgnI3vxfIHt4Tk72CKH86z_3F3E/edit?usp=sharing">Product Design with AI</a></p>
<hr>
<h2 id="youtube-playlist_2">YouTube Playlist <a class="head_anchor" href="#youtube-playlist_2">#</a>
</h2>
<iframe width="560" height="315" src="https://www.youtube.com/embed/videoseries?list=PLZJD9IHbt2T1-mjo3T17uSJUTVNY96Siu" title="YouTube video player"></iframe>
<hr>
<h2 id="reading-list_2">Reading List <a class="head_anchor" href="#reading-list_2">#</a>
</h2>
<ol>
<li><a href="http://www.amazon.com/Rebooting-AI-Building-Artificial-Intelligence-ebook/dp/B07MYLGQLB">Rebooting AI: Building Artificial Intelligence We Can Trust</a></li>
<li><a href="https://www.amazon.com/Mind-Motion-Action-Shapes-Thought/dp/046509306X">Mind in Motion: How Action Shapes Thought</a></li>
<li><a href="http://www.amazon.com/Alchemy-Curious-Science-Creating-Business/dp/006238841X">Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life</a></li>
<li><a href="https://www.amazon.com/Conscious-Brief-Guide-Fundamental-Mystery/dp/0062906712">Conscious: A Brief Guide to the Fundamental Mystery of the Mind</a></li>
<li><a href="https://www.amazon.com/Big-Nine-Thinking-Machines-Humanity/dp/1541773756">The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity</a></li>
<li><a href="http://www.amazon.com/You-Are-Not-Gadget-Manifesto/dp/0307389979">You Are Not a Gadget: A Manifesto</a></li>
<li><a href="http://www.amazon.com/Big-Disconnect-Protecting-Childhood-Relationships/dp/0062082434">The Big Disconnect: Protecting Childhood and Family Relationships in the Digital Age</a></li>
<li><a href="http://www.amazon.com/Stumbling-Happiness-Daniel-Gilbert/dp/1400077427">Stumbling on Happiness</a></li>
<li><a href="http://www.amazon.com/Ideas-Industry-Pessimists-Transforming-Marketplace/dp/0190264608">The Ideas Industry: How Pessimists, Partisans, and Plutocrats are Transforming the Marketplace of Ideas</a></li>
<li><a href="http://www.amazon.com/Hero-Outlaw-Building-Extraordinary-Archetypes/dp/0071364153">The Hero and the Outlaw: Building Extraordinary Brands Through the Power of Archetypes</a></li>
<li><a href="http://www.amazon.com/Diversity-Bonus-Knowledge-Compelling-Interests/dp/0691176884">The Diversity Bonus: How Great Teams Pay Off in the Knowledge Economy (Our Compelling Interests)</a></li>
<li><a href="http://www.amazon.com/Square-Tower-Networks-Freemasons-Facebook/dp/0735222916">The Square and the Tower: Networks and Power, from the Freemasons to Facebook</a></li>
<li><a href="http://www.amazon.com/Enlightenment-Now-Science-Humanism-Progress/dp/0525427570">Enlightenment Now: The Case for Reason, Science, Humanism, and Progress</a></li>
<li><a href="http://www.amazon.com/World-Beyond-Your-Head-Distraction/dp/0374535914">The World Beyond Your Head: On Becoming an Individual in an Age of Distraction</a></li>
<li><a href="http://www.amazon.com/Who-Gets-What-Why-Matchmaking/dp/0544705289">Who Gets What ― and Why: The New Economics of Matchmaking and Market Design</a></li>
<li><a href="http://www.amazon.com/Scale-Universal-Innovation-Sustainability-Organisms/dp/1594205582">Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies</a></li>
<li><a href="http://www.amazon.com/What-When-Machines-Everything-Algorithms/dp/111927866X">What To Do When Machines Do Everything: How to Get Ahead in a World of AI, Algorithms, Bots, and Big Data</a></li>
<li><a href="http://www.amazon.com/Fourth-Industrial-Revolution-Klaus-Schwab/dp/1944835008">The Fourth Industrial Revolution</a></li>
<li><a href="http://www.amazon.com/Silo-Effect-Expertise-Breaking-Barriers/dp/1451644736">The Silo Effect: The Peril of Expertise and the Promise of Breaking Down Barriers</a></li>
<li><a href="http://www.amazon.com/Sensemaking-Power-Humanities-Age-Algorithm/dp/031639324X">Sensemaking: The Power of the Humanities in the Age of the Algorithm</a></li>
<li><a href="http://www.amazon.com/What-Think-About-Machines-That/dp/006242565X">What to Think About Machines That Think: Today’s Leading Thinkers on the Age of Machine Intelligence (Edge Question Series) </a></li>
<li><a href="http://www.amazon.com/Overcomplicated-Technology-at-Limits-Comprehension/dp/1591847761">Overcomplicated: Technology at the Limits of Comprehension</a></li>
<li><a href="http://www.amazon.com/Emergence-Connected-Brains-Cities-Software/dp/0684868768">Emergence: The Connected Lives of Ants, Brains, Cities, and Software</a></li>
<li><a href="http://www.amazon.com/Whiplash-How-Survive-Faster-Future/dp/1455544590">Whiplash: How to Survive Our Faster Future </a></li>
<li><a href="http://www.amazon.com/Industries-Future-Alec-Ross/dp/1476753652">The Industries of the Future</a></li>
<li><a href="http://www.amazon.com/End-Average-Succeed-Values-Sameness/dp/0062358367">The End of Average: How We Succeed in a World That Values Sameness</a></li>
<li><a href="http://www.amazon.com/Undoing-Project-Friendship-Changed-Minds/dp/0393254593">The Undoing Project: A Friendship That Changed Our Minds</a></li>
<li><a href="http://www.amazon.com/Rise-Robots-Technology-Threat-Jobless/dp/0465097537">Rise of the Robots: Technology and the Threat of a Jobless Future</a></li>
<li><a href="http://www.amazon.com/Inevitable-Understanding-Technological-Forces-Future/dp/0525428089">The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future</a></li>
<li><a href="http://www.amazon.com/This-Idea-Must-Die-Scientific/dp/0062374346">This Idea Must Die: Scientific Theories That Are Blocking Progress (Edge Question Series)</a></li>
<li><a href="http://www.amazon.com/The-Innovators-Hackers-Geniuses-Revolution/dp/147670869X">The Innovators: How a Group of Hackers, Geniuses, and Geeks Created the Digital Revolution</a></li>
<li><a href="http://www.amazon.com/The-Idea-Factory-American-Innovation/dp/0143122797">The Idea Factory: Bell Labs and the Great Age of American Innovation</a></li>
<li><a href="http://www.amazon.com/Turings-Cathedral-Origins-Digital-Universe/dp/1400075998">Turing’s Cathedral: The Origins of the Digital Universe</a></li>
<li><a href="http://www.amazon.com/Flow-Psychology-Experience-Perennial-Classics/dp/0061339202">Flow: The Psychology of Optimal Experience (Harper Perennial Modern Classics)</a></li>
<li><a href="http://www.amazon.com/How-Create-Mind-Thought-Revealed/dp/1491518839">How to Create a Mind: The Secret of Human Thought Revealed</a></li>
<li><a href="http://www.amazon.com/Machines-Loving-Grace-Common-Between/dp/0062266683">Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots</a></li>
<li><a href="http://www.amazon.com/Jazz-Physics-Between-Structure-Universe/dp/0465034993">The Jazz of Physics: The Secret Link Between Music and the Structure of the Universe</a></li>
<li><a href="http://www.amazon.com/Intelligence-Jeff-Hawkins/dp/0805078533">On Intelligence: How a New Understanding of the Brain Will Lead to the Creation of Truly Intelligent Machines</a></li>
<li><a href="https://www.amazon.com/Myths-Live-Joseph-Campbell/dp/0140194614">Myths to Live By</a></li>
<li><a href="https://www.amazon.com/Big-Mind-Collective-Intelligence-Change/dp/0691170797">Big Mind: How Collective Intelligence Can Change Our World</a></li>
<li><a href="https://www.amazon.com/Reclaiming-Conversation-Power-Talk-Digital/dp/0143109790">Reclaiming Conversation: The Power of Talk in a Digital Age</a></li>
<li><a href="https://www.amazon.com/You-Belong-Universe-Buckminster-Fuller/dp/019933823X">You Belong to the Universe: Buckminster Fuller and the Future</a></li>
<li><a href="https://www.amazon.com/Metaphors-We-Live-George-Lakoff/dp/0226468011">Metaphors We Live By</a></li>
</ol>
<hr>
<h2 id="blogroll_2">Blogroll <a class="head_anchor" href="#blogroll_2">#</a>
</h2>
<ul>
<li><a href="https://garymarcus.substack.com/">Gary Marcus, The Road to AI We Can Trust</a></li>
<li><a href="https://aiguide.substack.com/">Melanie Mitchell, AI: A Guide for Thinking Humans</a></li>
</ul>
tag:notes.byed.it,2014:Post/ai-frame-and-perspective2023-06-24T04:57:48-07:002023-06-24T04:57:48-07:00AI: Frame and Perspective<p>Artificial intelligence will alter almost every industry in the coming year. Improving data technologies, faster computing, and a more receptive public will give way to new system models and tools we cannot yet imagine.</p>
<p>We have some things to do to clear the foggy mist over the current hype.</p>
<p>How do machines work?</p>
<p>Since the ENIAC (1946) invention, we have been programming machines to perform different tasks.</p>
<p>Before that point, tools like hammers or cranes could only do one thing. When a multipurpose machine was made available, we could suddenly write instructions for a machine to follow.</p>
<p>It was magical and must have felt like we got a new collaborator in the office – one is far more efficient and never complains.</p>
<p>That awe and our innate psychological biases to assign human-like attributes to machines (think of the last time you spoke to your car) inspired our early dreams of thinking machines.</p>
<p>This pursuit kept a generation of thinkers trying to untangle how humans think as the precursor to program machines who can do the same.</p>
<p>A further reading under this school of thought includes – but not be limited to – <a href="https://www.csee.umbc.edu/courses/471/papers/turing.pdf">Alan Turing</a>, Marvin Minsky (below), and <a href="https://www.youtube.com/watch?v=o86OLsbp40o">John McCarthy</a>.</p>
<p>The field carried on this trajectory through various dropouts in the budget and interest – commonly known as AI winters. But I want to get off this road for a moment and focus on the work of a different group of technologists.</p>
<p>IA (intelligence augmentation) looked at ways to celebrate human intelligence instead of trying to replace it.</p>
<p>How can we focus on a user, as extended by a machine - and not as an obstacle to its math?</p>
<p>Engelbart and Kay worked on developing the field in their respective labs at Menlo Park and Xerox Parc. The logic these teams have written is at the core of personal computing today. To the point of this piece, I want to land on the Dynabook.</p>
<p>The Dynabook was a hybrid of a laptop and an iPad. It was an early education device and needed to be user-friendly and intuitive - novel and non–existent ideas at the time.</p>
<p>To tackle that, Alan Kay invited Trygve Reenskaug to join his lab in California, and together with Adele Goldberg, they conceived of Model View Controller.</p>
<p>[Image by the author - based on a graphic from <a href="http://heim.ifi.uio.no/%7Etrygver/themes/mvc/mvc-index.html">MVC, Xerox Parc</a> 1978-1979](/_images/original_MVC_narrow.png)</p>
<p>Its original incarnation was genius. They were mapping computer models to users’ mental models. The idea of motivational frameworks was mainly reserved for psychologists and philosophers during that time, but those programmers and designers had the foresight to incorporate them into their products. And in a sense, inventing the science of user interface (for more proof of that, look no further than User Interface is Theatre).</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/GMDphyKrAE8?clip=Ugkx75ulG0zz3rf6jooOV_dfP0wUTmPsHWju&clipt=EOiJsgEYyN61AQ" title="YouTube video player"></iframe>
<p>In its later, more industrial version, Model View Controller lost a bit of its magic and became more of an efficient <a href="http://us9.campaign-archive2.com/?u=d2f457c304e680d6dca8147b0&id=c6b96875b3">Taylorist</a> equation.</p>
<p>[Industrial MVC](/_images/industrial_MVC_narrow.png)</p>
<p>Model View Controller was very well suited for the internet in its ability to break down information efficiently, hold together tidy databases, and build businesses that can monetize this ecosystem.</p>
<p>In an MVC system, the database is stationary, and the interface is proprietary.</p>
<p>What I mean by that is that your DB could be beyond compersion in size and complexity, but when you’re not moving your data, it is as stationary as books on shelves or bottles in a bar. It is the standstill model. Data is moved in and out by controllers.</p>
<p>The interface is proprietary because it lives in a domain (digital or physical) nurtured and controlled by a business. An app is groomed and maintained, optimized for every click and user action.</p>
<p><strong>Now comes the punchline:</strong></p>
<p>MVC is de facto the only server architecture we use. There is nothing else. Everything we do is based on stationary DB and proprietary interface points.</p>
<p>This is important because it can help us to unfold opportunities for true innovation and map current ones to this architecture.</p>
<h2 id="bots_2">Bots <a class="head_anchor" href="#bots_2">#</a>
</h2>
<p>Once we understand this underlying structure, we can quickly demystify bots. Those hyped–up voice-controlled interfaces are nothing more than interfaces.</p>
<p>What I mean by that is that, when it comes down to it, controllers are what does the work, the “magic.”</p>
<p>A controller will run <em>that</em> calculation for you, find a face of a friend in a photo, or reduce the speed of your self-driving car as you approach a turn.</p>
<p>The view is critical but a window – a relay point. Bots are nothing more than radio dials that use text.</p>
<p>Both text and voice interfaces are welcomed advancements in human-machine interactions – but they’re not AI.</p>
<h2 id="machine-learning_2">Machine Learning <a class="head_anchor" href="#machine-learning_2">#</a>
</h2>
<p>The structure is a crucial part of operating a program in computing and, more specifically, databases. You can’t run multiplications on a set of numbers and then find a letter.</p>
<p>Your system will fail. There are various gradients of data structure in the linkage between neat tables and a mishmash of words.</p>
<p>Machine learning can classify and organize this data into computer-friendly forms.</p>
<ul>
<li><p>Picture > faces, places, dates</p></li>
<li><p>Medical journals > concepts, doctors, citations, hypotheses, diagnosis</p></li>
<li><p>Road > lanes, cars, people in cars, speed of cards</p></li>
</ul>
<p>Back to MVC. We can think of machine learning (ML) as a patch to our database, taking in messy data and structuring it for better system performance and enabling new features. No magic involved, just statistics.</p>
<hr>
<p>I am excited about the industry starting a conversation about standard terms, users’ mental models, and a nuanced understanding of such a vast disruptor and opportunity.</p>
<p>Citing <a href="http://www.arbesman.net/overcomplicated">Samuel Arbesman</a>, we should not approach these systems with awe or fear.</p>
<p>We should know what we know and question what we don’t.</p>
tag:notes.byed.it,2014:Post/design-for-ai2023-06-24T04:48:00-07:002023-06-24T04:48:00-07:00Design for AI<h2 id="part-1_2">Part 1 <a class="head_anchor" href="#part-1_2">#</a>
</h2><h3 id="models-views-controllers_3">Models, Views, Controllers <a class="head_anchor" href="#models-views-controllers_3">#</a>
</h3>
<p>Model View Controller is a server architecture model invented at Xerox Parc in the late 70s. Initially, a system to implement graphic user interfaces for the desktop machine; it is now the core of practically anything we refer to as a digital product.</p>
<blockquote>
<p>“The essential purpose of MVC is to bridge the gap between the human user’s mental model and the digital model that exists in the computer. The ideal MVC solution supports the user illusion of seeing and manipulating the domain information directly. The structure is useful if the user needs to see the same model element simultaneously in different contexts and/or from different viewpoints. The figure below illustrates the idea.”</p>
</blockquote>
<p>— Trygve Reenskaug</p>
<p><a href="https://svbtleusercontent.com/4oRAMWwVq637DqcNeawpw40xspap.gif"><img src="https://svbtleusercontent.com/4oRAMWwVq637DqcNeawpw40xspap_small.gif" alt="8e71ff48-5664-485d-a08a-233b0369b0c6.gif"></a></p>
<p><a href="https://folk.universitetetioslo.no/trygver/themes/mvc/mvc-index.html">Origin of MVC</a></p>
<p>More concretely, the architecture illustrates the connection between intricate data sets and the intent of bridging the way humans and computers interpret data<sup id="fnref1"><a href="#fn1">1</a></sup>.</p>
<h2 id="mvc-today_2">MVC Today <a class="head_anchor" href="#mvc-today_2">#</a>
</h2>
<p><a href="https://svbtleusercontent.com/mBMq28YxNRgZmN9N3xRiah0xspap.png"><img src="https://svbtleusercontent.com/mBMq28YxNRgZmN9N3xRiah0xspap_small.png" alt="fc7679f5-d5ab-4a5b-a1a6-679f5bf706a9.png"></a></p>
<p>Source: <a href="https://developer.apple.com/library/ios/documentation/General/Conceptual/DevPedia-CocoaCore/MVC.htm">Apple Developer</a></p>
<h3 id="model_3">Model <a class="head_anchor" href="#model_3">#</a>
</h3>
<p>The model covers the core of the data structure. The logic embeds how different parts of the app will interact with that information. In the context of a web app, it will likely equal a database; for example, an archive of tweets, Wikipedia entries, address books, et al.</p>
<h3 id="views_3">Views <a class="head_anchor" href="#views_3">#</a>
</h3>
<p>The visual representation of the data once it made it to the user. A view results from a query the controller answers using data stored in the model—for example, a web page or a confirmation screen in an app.</p>
<h3 id="controller_3">Controller <a class="head_anchor" href="#controller_3">#</a>
</h3><h3 id="the-controller-is-the-link-between-the-user-a_3">The controller is the link between the user and the system (and also the core of the initial mission set by Reenskaug). A controller will respond to a query by executing a predetermined set of actions. <a class="head_anchor" href="#the-controller-is-the-link-between-the-user-a_3">#</a>
</h3>
<p>For example, ask the database for the information based on certain filters and then process that data to a view for the user. e.g. what I blogged on Jan 17th at 7.33 pm will render <a href="https://byed.it/at-7-33-08-pm">this link</a></p>
<p>Further reading: <a href="https://developer.apple.com/library/ios/documentation/General/Conceptual/DevPedia-CocoaCore/MVC.html">Apple Developer</a>, <a href="http://blog.codinghorror.com/understanding-model-view-controller/">Coding Horror</a></p>
<hr>
<p>Design for MVC</p>
<p><strong>MVC defines and drives our perception of what is a digital product (/system). It anchors the way design is taught and thought of.</strong></p>
<p>The diagram below is a simplistic view of an average design and development team mapped to an MVC model.</p>
<p><a href="https://svbtleusercontent.com/q42fGQoeTZzbkMh5KQd1D60xspap.png"><img src="https://svbtleusercontent.com/q42fGQoeTZzbkMh5KQd1D60xspap_small.png" alt="eb2ccb32-df1e-4223-9960-4df6e0987c76.png"></a></p>
<p>This is likely a defining experience for design as the shift from print to digital. We’re starting to design systems, quite literally, instead of views.</p>
<p>It is hard to illustrate the flow of data in a product entirely driven by AI, as this is still a significant variable, but I will make an honest attempt.</p>
<p>An MVC model has a timeline. Start. A query is asked. The controller engages the model to capture data and render a view. End.</p>
<p>We can conceptualize an AI system as a body of water (/data). It is sealed (past data) and bound by the design of its model. </p>
<p>Design for AI</p>
<p><a href="https://svbtleusercontent.com/8iiJGYiF8921dGpgqu4jGq0xspap.png"><img src="https://svbtleusercontent.com/8iiJGYiF8921dGpgqu4jGq0xspap_small.png" alt="3216d8f4-ca90-47af-999f-f5c12bb473bd.png"></a></p>
<p>A query will start a ripple effect. And as data processes, it corrects its speed through the <a href="https://en.wikipedia.org/wiki/Text_corpus">text corpus</a>. Each ring intact is better accuracy, more targeted assumptions made by the machine, and, most notably, better value for the user.</p>
<p>That single piece of design will need to encapsulate logic, data sets, goals, views, and much more. This metaphor reinforces the notion of depth. The deeper the reason, the better the reach of the ripple effect. And more value rendered for the user. On the same token, any discrepancies in that logic will be multiplied and will eventually render a product non–usable.</p>
<p><strong>This is a new way of thinking about products. Design. Type, color, and UI will be as crucial then as they are now, but we need a deep understanding of the problem to reach the logic required for such systems.</strong></p>
<h2 id="part-2_2">Part 2 <a class="head_anchor" href="#part-2_2">#</a>
</h2>
<p>The field of AI will bring together disciplines that traditionally had little overlap—education, psychology, math, technology, and philosophy. We don’t know what designing for AI will look like—but we do know that It will be different in just about every way from what we’re used to.</p>
<h2 id="systems-not-views_2">Systems, not Views <a class="head_anchor" href="#systems-not-views_2">#</a>
</h2>
<p>AI-driven products, will use different sets of moving parts, and a new type of relational logic. One way to untangle this problem is to find a familiar, ubiquitous element in today’s digital design and consider how likely it is to change.</p>
<p>MVC is a great place to start. The server architecture, invented in the 70s, is so ubiquitous now that it’s easy to underestimate how it formulates how we think. We’re accustomed to <strong>designing and monetizing views</strong>. The future will likely do more with <strong>holistic design</strong> work and a <strong>more significant focus on systems</strong>. Once we accept this premise, we can start exploring some of the exciting opportunities and responsibilities design for AI will entail.</p>
<h2 id="education_2">Education <a class="head_anchor" href="#education_2">#</a>
</h2>
<p>Design (and development) of AI will require decisions on datasets and the self–teaching mechanism itself. This is work on the shape, relationality, and feedback mechanism of a system that involved incredibly fast data processing with a person moving at their speed.</p>
<p>An algorithm, however brilliant it may be, will only be as bright as we allow it to be. Quality data is one part, but <strong>presetting</strong> it with the proper taxonomy and functions is crucial.</p>
<p>Let’s imagine a digital product and, for simplicity, focus on its data inputs, rendered outputs, and system algorithm.</p>
<p>What questions should we prepare ourselves to consider? </p>
<h3 id="data_3">Data <a class="head_anchor" href="#data_3">#</a>
</h3>
<p>What data sources are required to establish the <strong>logic that drives our product</strong>? Can we set a priority for those data sources (primary, secondary, and more)?</p>
<h3 id="function_3">Function <a class="head_anchor" href="#function_3">#</a>
</h3>
<p>Is that logic fixed or agile? What are the boundaries of its elasticity? We’re used to agility in views and features (essentially Models). Can we translate that to agile thinking? Our thinking and consideration of the algorithm itself?</p>
<h3 id="output-and-metrics_3">Output and Metrics <a class="head_anchor" href="#output-and-metrics_3">#</a>
</h3>
<p>What metrics would we be listening to? We know that accuracy and error rate are great ways of measuring the performance of AI.</p>
<p>It’s easy to grade the performance of tasks that we can do (for example, categorizing objects in view or even the more classic <a href="https://en.wikipedia.org/wiki/Turing_test">Turing test</a>, <strong>how do we grade generative procedures and machine-initiated ideas</strong>?</p>
<p>How do you measure the success of an idea? Especially when a person hasn’t set the problem? </p>
<h2 id="philosophy_2">Philosophy <a class="head_anchor" href="#philosophy_2">#</a>
</h2>
<p>Despite being very “new” and cutting edge, many guiding principles for determining a machine’s potential conciseness or capacity to learn have been front of mind for philosophers and mathematicians even before computers were digital. Some of these texts are valuable in establishing a language and a cognitive toolset for designers and thinkers to approach the topic.</p>
<ul>
<li><a href="http://www.csee.umbc.edu/courses/471/papers/turing.pdf">Alan Turing (1950), “Computing machinery and intelligence”</a></li>
<li><a href="http://philosophyfaculty.ucsd.edu/faculty/pschurchland/papers/sciam90couldamachinethink.pdf">Paul M. Churchland and Patricia Smith Churchland (1990), “Could a machine think?”</a></li>
<li>Recommended course: <a href="https://openlearninglibrary.mit.edu/courses/course-v1:MITx+24.09x+3T2019/about">EdX: Minds and Machines</a>
</li>
</ul>
<h2 id="psychology_2">Psychology <a class="head_anchor" href="#psychology_2">#</a>
</h2>
<p>Another exciting shift will be the lack of control over views. To render generative products, a designer must surrender control to the machine with a mutual understanding. That “contract” between the logic and program will need to contain a highly acute sense of the interactions we’re looking to foster.</p>
<p>We need to understand the core of the emotional mechanism driving a product. The better we can articulate, the better we can scale then. The more ambiguous we would leave them, the more they could spiral out of control.</p>
<h2 id="notes_2">Notes <a class="head_anchor" href="#notes_2">#</a>
</h2>
<div class="footnotes">
<hr>
<ol>
<li id="fn1">
<p><a href="https://heim.ifi.uio.no/%7Etrygver/2003/javazone-jaoo/MVC_pattern.pdf">Further reading: The Model-View-Controller (MVC) It’s Past and Present [PDF]</a> <a href="#fnref1">↩</a></p>
</li>
</ol>
</div>
tag:notes.byed.it,2014:Post/tools2023-06-23T06:04:58-07:002023-06-23T06:04:58-07:00Tools<p>An ongoing list of tools I often find myself sharing with people.</p>
<p>To Do’s</p>
<ul>
<li>
<a href="http://Asana.com">Asana.com</a> (cloud)</li>
<li>
<a href="https://culturedcode.com/things/">Things</a> (desktop)</li>
</ul>
<p>Writing</p>
<ul>
<li>
<a href="https://ia.net/writer">IA Writer</a> (desktop)</li>
<li>
<a href="https://paper.dropbox.com">Dropbox Paper</a> (cloud)</li>
</ul>
<p>Blogging</p>
<ul>
<li>
<a href="http://blot.im">Blot.im</a> </li>
</ul>
<p>Email</p>
<ul>
<li><a href="http://Buttondown.email">Buttondown</a></li>
</ul>
<p>Blogging + Email</p>
<ul>
<li><a href="http://Substack.com">Substack</a></li>
<li><a href="http://Write.as">Write.as</a></li>
</ul>
<p>Moodboarding/images</p>
<ul>
<li><a href="http://Anything.io">Anything.io</a></li>
</ul>
<p>Homepage </p>
<ul>
<li>
<a href="http://persona.co">persona.co</a> </li>
</ul>
<p>Contacts</p>
<ul>
<li>
<a href="http://Clay.earth">Clay.earth</a> </li>
</ul>
tag:notes.byed.it,2014:Post/versions-of-complexity2022-11-02T12:18:31-07:002022-11-02T12:18:31-07:00Versions of Complexity<p>I had the pleasure of co-teaching <a href="https://courses.newschool.edu/courses/PSDS2642">Complexity by Design</a> at Parsons SDM last semester and engaging with wonderful thinkers and institutes in this space. </p>
<p>It is becoming increasingly clear that complex thinking (definition to come later) is a core part of modern life. This was discussed in different circles before we all got into this state of unknowingness. </p>
<p>I have been working with a very acute definition of complexity, but given that the field is emerging (no pun intended), I wanted to linger a moment on its positionality.</p>
<hr>
<p>I have been working with 2.5 versions of complexity: a partial list of links and resources to follow.</p>
<h2 id="v1-scientific_2">V1: Scientific <a class="head_anchor" href="#v1-scientific_2">#</a>
</h2>
<ul>
<li><p><a href="https://www.santafe.edu/">Santa Fe Institute</a>, and their <a href="https://www.facebook.com/groups/santafeinstitute/">Complexity Explorers Group on FB</a> </p></li>
<li><p><a href="https://necsi.edu/">New England Complex Systems Institute</a></p></li>
<li><p><a href="https://cci.mit.edu/">MIT Center for Collective Intelligence</a> </p></li>
<li><p><a href="https://www.amazon.com/Scale-Universal-Innovation-Sustainability-Organisms/dp/1594205582">Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies</a></p></li>
<li><p>other topics include: chaos, fractals, bio-mimicry, modeling, <a href="https://ccl.northwestern.edu/netlogo/">netLOGO</a></p></li>
</ul>
<h2 id="v2-management_2">V2: Management <a class="head_anchor" href="#v2-management_2">#</a>
</h2>
<ul>
<li><p><a href="https://www.amazon.com/Jennifer-Garvey-Berger/e/B005GY5EG0%3Fref=dbs_a_mng_rwt_scns_share">Jennifer Garvey Berger’s books</a> </p></li>
<li><p><a href="https://hbr.org/2007/11/a-leaders-framework-for-decision-making">Cynefin Framework</a></p></li>
<li><p><a href="https://www.gse.harvard.edu/faculty/robert-kegan">Robert Kegan</a></p></li>
<li><p><a href="http://www2.econ.iastate.edu/tesfatsi/StandingOvation.MillerPage.pdf">The Standing Ovation Problem</a></p></li>
</ul>
<h2 id="v-25-selfleading_2">V 2.5: Self-Leading <a class="head_anchor" href="#v-25-selfleading_2">#</a>
</h2>
<p>A lot of the leadership advice, individuation, Jungian ideas of <a href="https://www.youtube.com/watch?v=1dOmrZZAodc">synchronicity</a>, and adjacent thinking on signifiers and semiotics are all very much complexity friendly.</p>
<p>Mostly because they accept the behaviorist nature of our world (<u>the noise in your head is different than mine</u>).</p>
<hr>
<p>My working list of axioms around complex systems is as follows: </p>
<ul>
<li><p>interconnected overrules design: they are not designable<br><br>
in fact: emergence (<u>‘it just happens…’ as one student informally articulated</u>) is the opposite of design</p></li>
<li><p>a system is as complex as we need it to be: we can exercise reduction if the situation allows and seek extra details (context) when the solution slides off the problem</p></li>
<li><p>complex systems are open-ended</p></li>
<li><p>hence a machine can never be truly intelligent, by the way (I recommend <a href="https://www.amazon.com/Rebooting-AI-Building-Artificial-Intelligence-ebook/dp/B07MYLGQLB">Marcus’ book</a> for those interested in that point)</p></li>
</ul>
<p>Complicated systems–like a car, computer program, or highway system–are an elaborate stacking of known constructs. </p>
<p>We can model the difference between complex and complicated as designing a highway system or designing fewer accidents.</p>
<p><u>p.s. I am sure I left links out; please comment with ideas and suggestions - I would love to add to this list.</u></p>
tag:notes.byed.it,2014:Post/80-20-aesthetics2022-10-21T10:18:58-07:002022-10-21T10:18:58-07:0080/20 Aesthetics <h2 id="the-market-for-creativity-ai-and-spreadsheets_2">The Market for Creativity, AI, and Spreadsheets <a class="head_anchor" href="#the-market-for-creativity-ai-and-spreadsheets_2">#</a>
</h2>
<p><a href="https://svbtleusercontent.com/uZqkK6JQTqqLQ8SNFUj1X70xspap.jpg"><img src="https://svbtleusercontent.com/uZqkK6JQTqqLQ8SNFUj1X70xspap_small.jpg" alt="31744563864_d548aa1d7e_o.jpg"></a></p>
<p><a href="https://flickr.com/photos/sdasmarchives/31744563864/in/photolist-QnabSC-RxAYWV-QeZEWq-R2axCt-QeW9rb-Qj19cc-LTSMiF-LnsLhJ-QiU1i8-LTyjaQ-Qg6sEc-N8rBzQ-JRDdMH-JwpP9U-S3zgUR-Rrfm6h-Qg3Fjs-Le8bef-RsPSH7-RsW1oq-fqHgoQ-Qg8J18-RxwW3X-NypteY-JfyFe1-QeWCmw-NBCvWM-HDfSWp-fqt1ED-oeFHpn-Rj3PRj-fqHfZq-QiTWV6-K6F93J-QdiQRS-fqHfZo-QVi4Rb-MkWprR-QWYkg5-QhE8qB-HCGKuL-fqt2qB-QVi4bd-PAgU3Q-Rj6EZf-RxJ5Tv-NBCmy8-QhDVrX-Qg9jfR-QY2WDY">Source</a></p>
<p>I am revisiting some thoughts on creativity and AI. In 2014/2015, I extensively researched AI, language, and system thinking (including an academic collaboration in computational linguistics and a <a href="https://www.youtube.com/watch?v=F0BbZRr8jbk">TEDx talk</a> on the topic). </p>
<p>Since then, I have shifted my writing to the psychology of creativity (going further into the augmentation side of the AI discourse) and now work as an executive creativity coach, running workshops on asking writing questions and developing ideas at the speed of clarity. </p>
<p>I am sharing some thoughts that might be useful for those looking to understand our moment and the space of possibilities.</p>
<h3 id="structure_3">Structure <a class="head_anchor" href="#structure_3">#</a>
</h3>
<p>A machine will better do anything structured better than a human.</p>
<p>A fixed relationship between variables is, in essence, a model and will continue to point in the direction of a decision. </p>
<p>It is up to a person to decide if finger-pointing (1) is sufficient and (2) can be autonomous. </p>
<h3 id="aesthetics_3">Aesthetics <a class="head_anchor" href="#aesthetics_3">#</a>
</h3>
<p>A Spreadsheet doesn’t have aesthetics. Not for its infinite monotony but because of stationary cells. Aesthetics requires adjusting the dynamic between objects of communication, and models can do none of that. </p>
<p>Another critical aspect for the creative to render is the ability to reflect, observe the observer, and see the water around the fish. </p>
<h3 id="scale_3">Scale <a class="head_anchor" href="#scale_3">#</a>
</h3>
<p>Algorithms deliver infinite scale, hence their popularity. It should be clear by now that aesthetics does not scale. </p>
<p>It might become a trend, but a trend is an echo of an aesthetic. And echoes fade. </p>
<h3 id="8020_3">80/20 <a class="head_anchor" href="#8020_3">#</a>
</h3>
<p>Borrowing from the 80/20 idiom: I want to propose one of thinking of algorithmic aesthetics. </p>
<p>As many thoughtful creatives are considering their feelings towards algorithmic design tools (an oxymoron that warrants a separate essay), I want to propose one way of linking the creative, rendered aesthetic, and scale.</p>
<p>As the creator creates, the shift from inner space to communication uses medium and language to bring form. That form is ready to be computerized because it has a structure and does not change in variables, the same way that Chess rules stay the same whether played by humans or on a room-sized computer. </p>
<p>If put to scale, there is a short period where aesthetics are passable until a moment when it diminishes (either by computer performance or cultural preferences). </p>
<p>At that point, ‘the jig is up,’ and a creative needs to create again. It is similar to the innovation cycle <a href="https://youtu.be/OUQEJW1oRuY?t=94">proposed by Geoffrey West</a>.</p>
<p>In the market of ideas, I propose that the ongoing balance between efficiency and creativity is profoundly personal and a form of aesthetic in and of itself. </p>
<p><strong>Deciding when the ‘jig is up’ makes all the difference.</strong></p>
<p>I know better than to make predictions. <br>
My intuition is that the market might split 80/20, where 80% will be OK with AI-made artwork, or algorithmic wardrobe, while 20% can see through the efficiency and the looming sameness. </p>
<p>Both sides will have a healthy balance of winners and losers, and in a way, nothing changes.</p>
<p>This moment, like the ones, even in the last couple of decades, asks us to philosophize about jobs, roles, and values taken for granted. It reminds us to understand the heavy lift in what we do and to put language on what makes us connect to others. </p>
<p>Algorithms that claim to be productive ask thoughtful users to bridge a space of creativity with those who ask for it.</p>
tag:notes.byed.it,2014:Post/common-dominator2019-01-01T16:58:10-08:002019-01-01T16:58:10-08:00Common Dominator<p>When designing for universality we design for a common dominator. Something we all do the same, a feature we all share (sit when we drive, walk on 2 legs). Reality then reminds us that universality is futile, we’re not all the same, and that if you look close enough the entire world is made of edge cases.</p>
<p>Once we get more personal with our constitutes (users, friends) it is easy to see that we’re all unique. In some way designing for a common dominator is like writing a script for a date beforehand, with a bunch of a if-then forks in your text.</p>
<p>Design for agency is like going to therapy. It is much more meta, and speaks to the forces of decision making and self fulfillment we all share.</p>
tag:notes.byed.it,2014:Post/mass-produced-software2018-12-31T04:32:20-08:002018-12-31T04:32:20-08:00Mass Produced Software<p>Mass produced software (MPS) is one that put the emphasis on the cranks and bolts of a large machines, that is hard to start and even harder to stop. It is about anomaly detection, about the reduction of individualism. About robots and humans that stand in lines, about hips of data perfectly pile up against a jig. </p>
<p>MPS is the opposite of the human sense making process. It is senseless. Like Soylent. It is purely utilitarian, and it waits for humans to make sense of it in the production side (brand) and consumption (meaning).</p>
<p>Context leads to more context. Radically contextual software (RCS) does not view context as a tangent from the assembly line, but the shortest path to meaning (and value). </p>
<p>RCS computes on the user end (edge computing), does not require a remote server by default, and is keen to think of itself as a single instance of utility (rather than a client to a mothership of a code base).</p>
tag:notes.byed.it,2014:Post/machine-to-human-instead-of-human-to-machine2018-12-30T15:58:58-08:002018-12-30T15:58:58-08:00Machine to Human, Instead of Human to Machine<p><a href="https://svbtleusercontent.com/k3T284gRsJyfiEo3gPLYHR0xspap.png"><img src="https://svbtleusercontent.com/k3T284gRsJyfiEo3gPLYHR0xspap_small.png" alt="E24BCBB2-9386-41CA-B358-86F246F5292E.png"></a></p>
<p>We could generalize software solutions as humans trying to find their way to a server. Through an iPhone app, a website, or a kiosk. The data is store remotely, the utility is hiding behind a propriety door (gatekeeper), the human is the one seeking that door, with a key (account, authentication), and behind that gated space the user’s data (& the system’s value) sits.</p>
<p>What can do to keep data user bound, with machines coming to meet the user where they are, with no data retention and paid for services?</p>
<p><a href="https://svbtleusercontent.com/cEmrFuXuKiZGQEAdndymWH0xspap.png"><img src="https://svbtleusercontent.com/cEmrFuXuKiZGQEAdndymWH0xspap_small.png" alt="3D9FEC27-FD27-4231-AAA5-B88CAAD3C16B.png"></a></p>
tag:notes.byed.it,2014:Post/goals-and-directions2018-12-30T15:40:18-08:002018-12-30T15:40:18-08:00Goals and Directions<iframe width="560" height="315" src="https://www.youtube.com/embed/Yw_2my5rZM4"></iframe>