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Rethinking the Intelligence of Machine Minds

Introduction

Although AI has been around since the 1950’s, advances over the past decade, particularly in machine learning, have brought about a radical-change in what we call AI.

With this “new AI” programmers no longer encode rules but instead build network frameworks. Then, using large quantities of data, the networks are trained and their components adjusted — or tweaked — until the system starts performing as desired.

Part of the magic, and the enigma, of AI is that we can’t open up a trained network to see what “rules” it has learned, because it doesn’t have any. Its understanding has developed organically, from the bottom up. …


On learning nature with AI.

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Big Data

We live in an age of scale. Of trillion dollar companies. Of social media followers measured in the hundreds of millions. Of efficiency, consumption, and greed being the greatest of our goals and ideals. And it is into this context that emerges a new technology: Artificial Intelligence.

AI seems perfectly aligned with our current moment, for it is built on the idea of scale — AI requires huge, almost unimaginable, amounts of data to learn and function. …


What happened to new media design?

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Untitled, 2015 (detail). Wade Guyton. From the series “The New York Times Paintings: November — December 2015”

I haven’t written to my blog, Inventing Interactive, for a while. This is because, in part, my work has shifted away from interactive and interaction design, and towards corporate user experience and innovation projects. But my frustration with the general state of the world, sometimes bordering on dispair, has also given me reason to pause. Pause not just from writing, but also from what I do. Over the past year I’ve returned to teaching in order to be more reflective on what design is and what it might become. And, with designing.ai, I’ve also been exploring what the future of design and artificial intelligence could be. …


This is a public-facing version of the reading list for the course Designing A.I. This may be updated over the course of the semester and will be supplemented by other readings posted to the course’s private Slack team.

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(Image: Jacqueline Casey)

Pre-Class [Week 0]

“The next wave of AI is rooted in human culture and history” (alternates to a tech-focused approach, and getting new perspectives in the future of AI)
https://www.engadget.com/2016/08/16/the-next-wave-of-ai-is-rooted-in-human-culture-and-history/

Technology (technical)

“Machine Learning: The New AI” (The MIT Press Essential Knowledge series), Ethem Alpaydin, 2016 https://www.amazon.com/dp/0262529513 or https://mitpress.mit.edu/books/machine-learning-1

“A Course in Machine Learning” Hal Daumé III
http://ciml.info

“Machine Learning: The Art and Science of Algorithms that Make Sense of Data”, Peter Flach…


These are the slides from the lecture introducing the course.

Below is a link to the Google Slides version of the presentation. The slide “notes” give credits and sources for the images and quotes.

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This is a public-facing version of the course syllabus. The reading list and weekly schedule are separate documents in the class’ Google Drive folder. Note that some of this may evolve or change over the course of the semester.

PSDS 5330, Spring 2017
Parsons School of Design, School of Design Strategies, Transdisciplinary Design Program

Faculty

David Young
Office hours on request

Course Description

Introduction

Emerging technologies are a significant driver of what and why we design. But technologies don’t develop in isolation. They are influenced and shaped by how we choose to utilize and engage with them. Design connects new technologies to unmet user needs — discovering unimagined opportunities and creating innovative products, services, and platforms. …


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For more information see The New School course catalog description: https://courses.newschool.edu/courses/PSDS5330

Artificial Intelligence (A.I.) technologies are on the verge of going mainstream; but how they will ultimately manifest is an open question.

This studio will examine current and near-term A.I. from the perspective of an underserved, alternative, or creative community. Taking that community as a partner, students will explore how A.I. could be applied in service to the aspirations of that group.

In this course you will:

  • Survey the current landscape of A.I. technologies and the surrounding questions of social bias.
  • Develop new ways for non-technical stakeholders to benefit from, and contribute to, emerging technologies. …


On diversity, design methods, and shaping the future of an emerging technology.

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The Reemergence of A.I.

Every day we read about new developments in Artificial Intelligence (A.I.). Significant advances in machine learning, natural language processing, image recognition, and a myriad of other A.I. technologies are being used to solve previously insurmountable problems. And although these technologies are still in their infancy, there is a strong belief that they will radically disrupt much of how we see and engage with the world. There is a seeming inexorable march of this technology, with near-future uses that border on the fanatastical.

But A.I. technology’s futures are neither inevitable nor singular. Technology is human — it is developed and advanced by the people that create, use, and promote it. This enables a wide range of simultaneous discoveries and innovations — from the broad initiatives of businesses and governments, to the experimentations of researchers and makers. These, in turn, inform, inspire and guide how technology is advanced, and where our cultural, civic, and businesses resources and efforts are prioritized. …


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We’ve heard plenty from pollsters, pundits and politicos on what people think about Hillary Clinton and Donald Trump, but what does an A.I. (artificial intelligence) think of them?

But some background first. Why am I doing this? A.I. is an emerging technology that’s on the verge of being deeply incorporated into much of our daily lives. Its impact will be widespread and profound — and potentially invisible. I’m interested in understanding and influencing the design of new and innovative ways that it can be used — enabling all people to understand its impact, and help give voice to its development. …


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When I was an undergrad my favorite course was Introduction to AI, taught by Ira Pohl. When I graduated, I went to work in the AI department at BBN. I was working on, then state-or-the-art, projects involving machine learning, genetic algorithms, and expert systems.

But that work, in the 80s, the end of a boom period for AI, felt very theoretical and researchy/experimental. The field was trying to develop real-world applications with technology and approaches that were in their infancy and sometimes a little rickety. I decided to move on and explore the creative intersections of design and technology.

Cut to today, early-2016, and suddenly AI is popping up everywhere. The field has transformed and, with recent breakthroughs, there is a real sense that AI is about to lead the next big technology transformation. Chris Dixon, in his post What’s Next in Computing? argues that this change will be as significant as the shifts that occurred after the introduction of the PC, the Internet, and Mobile. …

About

David Young

Art and AI. www.triplecode.com

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