Celebrating good things
A pat on the back to a great team.
A pat on the back to a great team.
"Hashes can help show when data has been changed. Even when the source data changes slightly, its hash will change significantly. David Marques/@projectsbyif” https://t.co/a7dzsKYWyI
— John Maeda (@johnmaeda) July 25, 2019
Video: Displaying two identical texts and showing when it is modified the hash code will differ. pic.twitter.com/cmxsye4hKw
“By helping people understand how decisions are made, they have more agency within the system” ✊@GAnnanCallcott @akilbenjamin #AfroTechFest pic.twitter.com/lWnzlEQ83l
— Maria Izquierdo (@izdo_maria) April 12, 2019
Sarah Gold, who founded If to help companies use data more ethically, thinks that as customers become increasingly savvy about data politics, brands will have to be more transparent about how they collect it https://t.co/OffyeWf4W6 pic.twitter.com/5D3mF7VMhj
— Creative Review (@CreativeReview) April 11, 2019
.@fitzsimple explaining the ethical and trust dilemmas in #NewTech @Pioneers in #Vienna #Rathaus pic.twitter.com/TOmo4jh1TT
— Neil Walsh - UN (@NeilWalsh_UN) April 2, 2019
Patterns catalogue featured in John Maeda's Design in Tech report for 2019 - March 2019
Maria speaking about IF's work all the way from Zaragoza! – March 2019
Photo by Grace Annan-Callcott
Learnt loads from @raemond, and was inspired by @projectsbyif people in a housing data workshop, well in the bits where I managed to stop myself talking.
— Paul Downey (@psd) January 24, 2019
To make technology work in service to people, society needs to be able to hold systems that use machine learning to account. We’re here to make that happen 🔥🔥@ohrworm @citizenbeta pic.twitter.com/uyJPirlA5q
— IF (@projectsbyif) 3 December 2018
We'd like one of these for our birthday please! – December 2018
Photo by Grace Annan-Callcott
Celebrating turning 3! – December 2018
Photo by Isabel Izquierdo
🧠@fischerfel (@ProjectsbyIF) writes about how #MachineLearning systems constantly learn from #data about people to optimise themselves. He asks: what if inputs contain very sensitive information or even secrets?https://t.co/sq7kK4r7VO #AI pic.twitter.com/vnJV6lmFSX
— CognitionX (@cognition_x) 29 November 2018
Great explainer of how machine learning models can leak personal data, (featuring work from @mikarv, @lilianedwards and myself) https://t.co/l5lYXr1k57
— Reuben Binns (@RDBinns) 29 November 2018
Next up @izdo_maria from @projectsbyif explains how as automation becomes more widespread, we increasingly need to design for machines as well as humans pic.twitter.com/WqkT0GqgMp
— DataKind UK (@DataKindUK) 28 November 2018
Really enjoying first week of full-time work @projectsbyif. Brilliant, nice people. Interesting projects. And I've snagged a space heater all to myself. What's not to love?
— Ella Fitzsimmons (@fitzsimple) 19 November 2018
Our friends at @projectsbyif have a great exhibition running at the moment on understanding automated decisions. It finishes tomorrow, so catch it if you can - Andrewhttps://t.co/2xBrok7zq5
— DeepMind Health (@DeepMind_Health) 8 November 2018
Launching our exhibition with Alison and the LSE Data and Society programme on explainability in machine learning – October 2018
Photo by Grace Annan-Callcott
I like this a lot. It's crucial to cut down on fuzzy language around automation. #UADproject https://t.co/c9xQCndrus
— Charlotte Jee (@charlottejee) 29 October 2018
Nat wrote up some exciting work we've been doing with DeepMind using Trillian. - October 2018