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/
There is a 100-year history of flu pandemics causing long-term neurological problems (tweet from March 2020) 3/
The 1918 flu pandemic was a mass-disabling event (links at bottom of thread) 4/
Myalgic encephalomyelitis patients have been warning us for decades about post-viral disability & chronic illness (tweet from march 2020) 5/
Why is it so hard for countries to learn from each other and from history? My thoughts: 6/
1. Many people fundamentally don’t understand exponential growth and still can’t imagine it. They believe they can keep covid at a “manageable” level without extensive, multi-pronged interventions. 7/
2. Short-term thinking. The pain or inconvenience of the present (lockdowns, masking, etc) clouds out longer-term thinking (collapsed hospital system, widespread disability from long covid, deaths) 8/
3. If precautions help avert disaster, the precautions are then seen as unnecessary by many, b/c the warned-about disaster didn’t happen. 9/
4. Psychologically, many are unable to grasp their own mortality & vulnerability. They falsely believe because they have always been "healthy" in the past, they won't get long covid, they will never be disabled, they are invulnerable. 10/
This is also linked to myths around worth & disability: that the disabled must have done something wrong, that if they just changed their diet/tried yoga/found the right doctor/etc, they could recover. 11/
5. Science is messy & nuanced. "Let’s just get to 70% adults vaccinated!" (56% of population) is much catchier than "we need a multi-pronged approach of better ventilation, better fitting masks, rapid antigen testing, AND 90% vaccinated, including on sub-populations" 12/
Great article on the messiness of the scientific process, the difficulty of measuring things 13/

6. Wishful thinking. Many want their old lives back, and may misdirect their anger. Many have not had a way to process the trauma, grief, & anger of the last 18 months, nor reach acceptance that this is not 2019 anymore. 14/
7. Poor public health messaging. There has been some terrible public health messaging in the past 18 months (Only elderly will die! Repeated flip-flopping on masks. Still emphasizing hand sanitizer & ignoring ventilation), which has made all of this harder to grasp. 15/

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More from @math_rachel

13 Sep
[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 The epistemology problem stems from a series of assumptions
"...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 epistemology problem stems from a series of assumptions
"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/ What does this mean for the goose presently laying all the g
Read 4 tweets
25 Aug
75% of people aged 16+ in UK have both doses of covid vaccine & there are currently 700 covid deaths PER WEEK in UK

Some Aus leaders want to reopen when vaccines for ages 16+ hit 70-80%. If our death rate is proportionate to UK, that would mean 266 Australians dying PER WEEK. 1/
Many in UK have already had covid, so it's likely that the AUS death rate could be higher than that 266 ppl per week

75% of ppl 16+ is only 60% of the whole population. 60% against Delta is not enough. We need to vaccinate children & we need rates ~90%. 2/
Some point out how society accepts deaths from flu. In 2019, there were 486 flu deaths in Australia (averages to 9 per week). 2017 was particularly bad with 1,255 flu deaths (avg 24 per week).

What we are facing with covid is over 10x more. These are not the same. 3/
Read 4 tweets
19 Aug
I’m hearing more people in Australia talk about wanting to "live with Covid", even though only 22% of the population is fully vaccinated. #LivingWithCovid (combined with low vaccination rates) means… 1/
Living with Covid (+ low vaccine rates) is:
- Delaying surgery for cancer, organ transplants, brain tumors
- waiting an hour to get an ambulance after heart attack
- turning medical emergency into a catastrophe, b/c the hospital is maxed out
- millions disabled with LongCovid 2/
Living with covid is not just the death count, it is 10-30% of so-called "mild" cases becoming permanently disabled with LongCovid, which can include debilitating neurological effects and constant pain. 3/

financialpost.com/news/economy/l…
Read 7 tweets
19 Aug
An overall lack of recognition for the invisible, arduous, & taken-for-granted data work in AI leads to poor data practices, resulting in data cascades (negative, downstream events)... “Everyone wants to do the model work, not the data work” 1/

storage.googleapis.com/pub-tools-publ… Incentives and currency in AI An overall lack of recognition
Paradoxically, data is the most under-valued and
de-glamorised aspect of AI

--Everyone wants to do the model work, not the data work: Data Cascades in High-Stakes AI by Nithya Sambasivan @shivanikapania Hannah Highfill @NaaShomeh @heuristicity @laroyo 2/
research.google/pubs/pub49953/ Data Cascades in High-Stakes AI Nithya Sambasivan, Shivani K
Data quality issues in AI are addressed with the wrong tools created for, and fitted to other tech problems—they are approached as a database problem, legal compliance issue, or licensing deal. 3/ Considering the above factors, currently data quality issues
Read 8 tweets
17 Aug
5 Myths of Co-Design for Ethical ML
- ‘Better’ involvement➡️ 'better’ design outcomes
- Co-design increases agency of patients
- Representation reduces risk of harms
- Co-design is an inherently ethical approach
- All problems can be co-design problems
@josephdonia @jayshaw29 1/ Co-design and Ethical Artif...
Novel challenges when co-designing AI:
- participation is often unwitting (eg as training data)
- AI technologies can be repurposed after deployment
- black box nature
- hard to account for how data produced by system will be used in future 2/ Claims to the normative sup...
"Better" involvement does not imply a stronger focus on the whole system (including consequences related to data commodification & surveillance), much of which is out of view for both users & designers 3/ Myth #1: ‘Better’ involveme...
Read 6 tweets
6 Jul
The orgs in his thread are excellent, but it is hypocritical and downright harmful for Jeff Dean to share them like this. 1/
Jeff even includes Black in AI, a fantastic org co-founded by @timnitGebru, whom he fired and then tried to portray using the angry Black woman trope. 2/

venturebeat.com/2020/12/10/tim…
One of the 3 conflicting stories that Google has provided about why Dr. Gebru was fired is that it was for being honest about how working on diversity initiatives at Google made her life HARDER. 3/

Read 6 tweets

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