NIPS 2016 Symposium on People and machines: Public views on machine learning, and what this means for machine learning researchers
Hover over the left for a table of contents. These hastily-captured notes are not accurate; they are paraphrase and may contain inaccuracies, typos, and falsehoods. Importantly, they may not reflect the true intent of the speaker. I apologize for any inaccuracy.
Susannah Odell: Public perception surveys and storytelling for professional communication
(missed the first part of this talk and its title!)
9% of people in the UK have even heard of the term"machine learning"
…but 70% have heard of computers that could understand human language and could answer human questions
…and 75% have heard of driverless vehicles.
75% get information from mainstream media(tabloids?),
21% get info from entertainment(Westworld? Black Mirror?)
But they do see applications.
Where do people think machine learning could be helpful?
Recommendation
For doctors
Improving education
Tackle global challenges
Aging population
People have questions and concerns about machine learning
Algorithms should be safe and trustworthy
People want to know that they won't be replaced by machines
They don't want these algorithms to be making decisions that could have a real impact on their life, or label them in a way that prevents them from doing something down the life
How can we address these concerns?
Connecting directly with the public(see what the Royal Society is doing)
WE are the ones who need to be helping! Expert view, demystifying technology. Talk to people: policy makers, users, future generation, investors, taxpayers, funding agencies.
If you engage with the public in a human-readable format(such as a blog post), it makes your research more visible.
Blog posts have high visibility because they become the main point of communication
Research is more accurately portrayed
Helps with citations
Increases opportunities(speaking, …)
Growing your network
Helps you understand your field, shape your own ideas, practice communication skills
Allows you to raise funding
Have your opinion heard
There are a tremendous number of reasons to be communicators.
And there are a tremendous number of reasons why we don't do it.
We don't know how to use modern communication tools;
Communicating effectively is a time sink;
Don't have a platform(tools like Twitter help with this)
What can you do to make your own document more human-readable?
NIPS 2016 Symposium on People and machines: Public views on machine learning, and what this means for machine learning researchers
Susannah Odell: Public perception surveys and storytelling for professional communication