Raw data is both an oxymoron and a bad idea; to the contrary, data should be cooked with care.
Absolutely spot on! And it cuts both ways:
A terrific cautionary look at the history of machine learning and artificial intelligence from the new laugh-a-minute book by James.
An even-handed assessment of the benefits and dangers of machine learning.
It’s upsetting to realize that the reason why you’re in a senior position may be because of the system of privilege that got you there. It’s upsetting to realize that there are people who aren’t in that rank who are more qualified than you, but who haven’t benefited from the same privilege you did.
So here’s what I can do about it:
- Start sponsoring members of underrepresented groups
- Listen to marginalized people, and believe them
- Do “the homework” to be a better mentor
Cennydd is writing (and self-publishing) a book on ethics and digital design. It will be released in September.
Technology is never neutral: it has inevitable social, political, and moral impact. The coming era of connected smart technologies, such as AI, autonomous vehicles, and the Internet of Things, demands trust: trust the tech industry has yet to fully earn.
Why building inclusive tech takes more than good intentions.
When we run focus groups, we joke that it’s only a matter of seconds before someone mentions Skynet or The Terminator in the context of artificial intelligence. As if we’ll go to sleep one day and wake up the next with robots marching to take over. Few things could be further from the truth. Instead, it’ll be human decisions that we made yesterday, or make today and tomorrow that will shape the future. So let’s make them together, with other people in mind.
If research on biases has told us anything, it is that humans make better decisions when we learn to recognize and correct for bias.
A series of questions to ask on any design project:
- What are my lenses?
- Am I just confirming my assumptions, or am I challenging them?
- What details here are unfair? Unverified? Unused?
- Am I holding onto something that I need to let go of?
- What’s here that I designed for me? What’s here that I designed for other people?
- What would the world look like if my assumptions were wrong?
- Who might disagree with what I’m designing?
- Who might be impacted by what I’m designing?
- What do I believe?
- Who’s someone I’m nervous to talk to about this?
- Is my audience open to change?
- What am I challenging as I create this?
- How can I reframe a mistake in a way that helps me learn?
- How does my approach to this problem today compare to how I might have approached this one year ago?
- If I could learn one thing to help me on this project, what would that one thing be?
- Do I need to slow down?
A great short talk by Tim. It’s about performance, but so much more too.
When it seems like all our online activity is being tracked by Google, Facebook, and co., it comforts me to think of all the untracked usage out there, from shared (or fake) Facebook accounts to the good ol’ sneakernet:
Packets of information can be distributed via SMS and mobile 3G but also pieces of paper, USB sticks and Bluetooth.
Connectivity isn’t binary. Long live the papernet!
A look at our inbuilt confirmation biases.
Jason Kottke on the still-ludicrous imbalance at most tech conferences. This issue isn't going to go away. Conference organisers need to stop being part of the problem and become part of the solution.