Design Despite Disciplines

Berkeley MDes

8 Episodes

Given the opportunity, designers will endlessly debate.

Perhaps this is because practices of design fundamentally disagree. We can see this in the hotly contested differences that delineate design movements, and disciplinary boundaries that are continuously in flux. However, we may also see that there are ways of thinking and knowing common across designers.

This podcast series seeks to uncover the most pressing debates that go beyond design practices. Design Despite Disciplines is hosted and produced by the Berkeley MDes course, Debates in Design. To learn more, visit design.berkeley.edu.

Podcasts Similar to Design Despite Disciplines

Computer Science (95.46%)

Oxford University

Pondering AI (94.89%)

Kimberly Nevala, Strategic Advisor - SAS

No Bias (94.86%)

No Bias

Artificiality (94.79%)

Sonder Studio

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) (94.67%)

Sam Charrington

ICSTI Winter Workshop (94.56%)

UPMC

The Analytical Wavelength (94.43%)

ACD/Labs

DataLab: The Materials Informatics Podcast (94.42%)

DataLab Materials Informatics Podcast

TDSlowdown (94.4%)

Henrik Sætra

Colper Science (94.35%)

Kambiz Chizari, Ilyass Tabiai

How do you know? (94.24%)

Christie Bahlai

Creative Courage (94.14%)

Jules Padova & Neha Gajbhiye

Gradient Dissent (94.13%)

Lukas Biewald

Machine Learning Bits (94.08%)

Youness ECHCHADI

Data & Society (94.0%)

Data & Society

Exploiting with Teja Kummarikuntla (93.97%)

Teja Kummarikuntla

Beyond Numbers: Covid19 and Society (93.86%)

COVINFORM project

The Turing Podcast (93.83%)

The Alan Turing Institute

Sound and Data (93.8%)

Scot Gresham-Lancaster

AI+Design (93.77%)

VSA Partners

Super Position (93.75%)

Super Position

Future of Science by DeSci Foundation (93.74%)

DeSci Foundation

PLN8 (93.73%)

Stamen Design

convergeML (93.72%)

convergeML

Towards Data Science (93.69%)

The TDS team

NSF Rapid Response COVID-19 (93.65%)

National Science Foundation

How AI Happens (93.63%)

Sama

The Mathematics of Machine Learning - A Research Conference of the Cantab Capital Institute for the Mathematics of Information (93.54%)

Cambridge University

Practical AI: Machine Learning, Data Science (93.5%)

Changelog Media

Vanishing Gradients (93.49%)

Hugo Bowne-Anderson

UC Berkeley School of Information (93.47%)

School of Information, UC Berkeley

Department of Statistics (93.35%)

Oxford University

Machine Learning Engineered (93.27%)

Charlie You

Data Skeptic (93.19%)

Kyle Polich

Essay4Students (93.17%)

None

This Might Not (93.16%)

Sean Kearney

Explore Explain (93.16%)

Andy Kirk

Women in AI (93.14%)

RE•WORK

The Mathematics of Deep Learning and Data Science (93.13%)

Cambridge University

Jisc sessions (93.11%)

Jisc

DigiTalk Pod (93.11%)

Chalmers Production Area of Advance

McKinsey on AI (93.09%)

McKinsey Analytics

Astrix Digital Transformation Podcast (93.07%)

Kevin

Learning Better and Faster (93.06%)

MLearning.ai

DataNBots (93.02%)

DataNBots

Flush to Data (92.98%)

Kris Villez and Jörg Rieckermann

Digital communications - for iBooks (92.95%)

The Open University

Data Science at Home (92.94%)

Francesco Gadaleta

What is it about computational communication science? (92.92%)

Emese Domahidi & Mario Haim

Austrian Ai Podcast (92.91%)

Manuel Pasieka

machinelrn (92.86%)

machinelrn

Type Cast Heroes (92.84%)

Type Cast Heroes

Diaries of Social Data Research (92.78%)

Katherine A. Keith & Lucy Li

Within & Between (92.73%)

Within&Between Podcast

The Machine Learning Podcast (92.73%)

Tobias Macey

IS 301 course podcasts & RSS feeds by Prof. Ed Nickel (92.71%)

None

The Machine Listening Podcast (92.68%)

Audio Analytic

Stanford MLSys Seminar (92.67%)

Dan Fu, Karan Goel, Fiodar Kazhamakia, Piero Molino, Matei Zaharia, Chris Ré

Project X Discussions (92.67%)

None

The Human and Machine Podcast (92.67%)

Element8

EXALT (92.66%)

EXALT

Open Science Stories (92.64%)

Heidi Seibold

HumAIn Podcast - Artificial Intelligence, Data Science, Developer Tools, and Technical Education (92.63%)

David Yakobovitch

Not Loud Enough Podcast (92.62%)

Canan Marasligil & Laura M. Pana

There's So Much We Don't Know (92.58%)

Meghan Maureen and Nick Foy

Ringvorlesung - Database Research (WT 2021/22) - tele-TASK (92.58%)

various lecturers

Bad Faith Cycles in Algorithmic Cultivation (92.56%)

Calvin H

Open Access Audio Abstracts (92.55%)

Lara

The Minhaaj's Podcast (92.49%)

minhaaj rehman

The AutoML Podcast (92.47%)

AutoML Media

Robert Smith's Podcast (92.45%)

Robert Smith

Behind the Data (92.42%)

Behind The Data

TYPES OF ARTIFICIAL INTELLIGENCE (92.41%)

Dev

Machine-Centric Science (92.39%)

Donny Winston

Collective Intelligence Network (92.36%)

Adam McKenty

Inverse Problems Network Meeting 2 (92.33%)

Cambridge University

Living Digital (92.32%)

Schlumberger Software

Core Dump (92.31%)

Luís Marques, Rita Morais

Artificial Intelligence Podcast - Statisfai (92.28%)

Artificial Intelligence Podcast - Statisfai

Change Management Podcast by The Change Compass (92.27%)

The Change Compass

OII Bellwether Lectures (92.21%)

Oxford University

Behind Data Science (92.21%)

Big Cloud

The Minerva PLM TV Podcast (92.21%)

Jennifer Moore

Absolute AI (92.2%)

Innodata

QuantumBlack Voices (92.19%)

QuantumBlack

Raising Heretics, the Podcast (92.19%)

Dr Linda McIver

KLING KLANG KLONG (92.18%)

Kling Klang Klong

Cambridge-INET Institute Conversations in Economics (92.18%)

Cambridge University

Oversimplified (92.16%)

Conor Dewey

The Vocabulary of Big Data (92.14%)

Cambridge University

Edge & Main (92.13%)

futureofgood

Chai Time Data Science (92.12%)

Sanyam Bhutani

Origins: Explorations of thought-leaders' pivotal moments (92.11%)

Ryan McGranaghan

Digital Future Society (92.08%)

Digital Future Society

Machine Ethics podcast (92.07%)

Ben Byford and friends

FAIR Data Podcast (92.07%)

FAIR Data Podcast

Humans, Data and Machines (92.07%)

None

Women in Data Science (92.05%)

Professor Margot Gerritsen, Cindy Orozco Bohorquez

Ethics of AI in Context (92.03%)

Ethics of AI Lab, University of Toronto

Methods (92.03%)

National Centre for Research Methods