"My concern is that reducing humans to acting as data sources is fundamentally inhumane."
-- Alan Blackwell 1/ dl.acm.org/doi/abs/10.714…
"But whereas the core problem of symbol-processing AI was its lack of connection to context – the problem of situated cognition – the core problem of machine learning is the way in which it reduces the contextualised human to a machine-like source of interaction data." 2/
The user is effectively submitting to a comparison between their own actions and those of other people from which the model has been derived. In many such comparisons, the effect will be a regression toward the mean. 3/
If the user wishes to control or modify the model's behavior, they must do so at one remove, by modifying the data rather than the model. The user must second-guess an inference algorithm, trying to select the right combination of data to produce a model to fit their needs. 4/
Above quotes from "Interacting with an Inferred World: The Challenge of Machine Learning for Humane Computer Interaction" by Alan F. Blackwell
When patients reject a mental health (mis)diagnosis for symptoms they know have physiological origins, it is *not* bc they are devaluing mental health.
Patients do this bc they know that it will lead to ineffective treatments & useless research. 1/5
There's a pernicious cycle: label a poorly understood illness as psychogenic ➡️ don't invest money in researching the physiological origins ➡️ claim the lack of evidence on physiological mechanism proves it's psychogenic ➡️ repeat
2/5
Bonus: if patients are not "rational" enough in their suffering as medical establishment offers them nothing ➡️ use this as further evidence that their symptoms can't have physiological origins 3/5
Medicine, like all of science, is political:
- which questions get asked
- which projects get funded
- how debates get framed
- who the researchers are
- context of data (what categories, what labels, which biases, what is left out)
- whose suffering is counted 1/
Science does not just progress inevitably, independent of funding and politics and framing and biases. 2/
Activists of ACT UP pushed USA govt & medical establishment to stop ignoring HIV/AIDS in the late 80s/early 90s, and to invest more in researching & addressing it. The huge progress that has happened in HIV/AIDS research & treatment would not have happened otherwise. 3/
Queensland police to trial AI tool designed to predict and prevent domestic violence incidents. This raises a number of concerns 1/ theguardian.com/australia-news… h/t @benhutchinson
The police superintendent says that they have removed raw data about ethnicity and geography as part of effort to avoid bias.
This does not prevent bias, at all. Machine learning is all about picking up latent variables. More on this topic: 2/
Corporate-funded efforts to downplay covid are using strategies straight out of the climate denial playbook, funding contrarian scientists, misleading petitions, social media bots,...
In many cases, it is literally the same billionaires & corporations funding climate change denial and covid minimization, opposing public health measures 2/
It is critical for physicians, scientists, & public health officials to realize that they are not dealing with an orthodox scientific debate, but a well-funded sophisticated science denialist campaign based on ideological & corporate interests 3/
[Faulty] assumptions in design & deploy of AI systems:
- user is an individual
- individual prioritizes personal well-being
- text & context can be separated
- the only useful knowledge is that produced through rational instrumentality... jasonedwardlewis.medium.com/from-impoveris…@jaspernotwell
"...This makes AI system engineers blind to vital aspects of human existence — such as trust, care, and community — that are fundamental to how intelligence actually operates." 2/
"The people who produced that data were not asked if it be used this way, they were not compensated for this use, & the use does not benefit them directly.
Indigenous communities have long histories with people like this. We recognize them for what they are: colonizers" 3/
One depressing aspect of the pandemic is how countries refuse to learn from other countries. Within a country, states refuse to learn from other states. Many refuse to learn from history. Many believe in exceptionalism, that they won’t face what everyone else has. 1/
I still remember first seeing the images of tent hospitals in Lombardy and realizing that this could happen everywhere. Jeremy & I did a data analysis and wrote at the time 2/