dan mcquillan

dan mcquillan.png

intro’d to Dan here (via Maha):

ℳąhą Bąℓi, PhD مها بالي  (@Bali_Maha) tweeted at 5:43 AM – 9 Jun 2019 :
This is among the *best* critique of AI/analytics I have ever read @14prinsp @KateMfD @Czernie @gsiemens https://t.co/K8tWYtK8Ug(http://twitter.com/Bali_Maha/status/1137686601662959621?s=17)

article by @danmcquillan

Machine learning extends bureaucracy into the future;
or rather, it bureaucratises a probabilistic future and actualises it in the present.

too much ness

A human-in-the-loop is not a humanistic pushback
as that human is themselves subsumed by the institution-in-the-loop.

broken feedback loop

They (people’s councils) are a collective questioning
of the decisions that define the way the machines will make decisions,
by applying critical pedagogy and situated knowledge.

They constitute a different subjectivity –
iterative deliberation of consensus, done right,
is an antidote to bureaucracy and to the calculative iterations of machine learning

public consensus always oppresses someone(s)..

let’s listen to curiosity first.. consensus become irrelevant

We need to develop a different order of ordering.
Instead of ways of organising that allow everyone to evade responsibility,
we need to reclaim our own agency through self-organisation..t

2 convers as infra

We need to think collectively about ways out of this mess,
learning from and with each other rather than relying on machine learning.
countering thoughtlessness with practices of collective care.

listen to and facil daily curiosity  ie: cure ios city

We can’t uninvent either AI or bureaucracy,
but we can choose to radically change both our modes of organisation
and our approach to computational learning.

ai humanity needs.. augmenting interconnectedness


3 min interview from 2018 [https://vimeo.com/262354951]

mainly because they are such an efficient mech for classification and targeting.. a mech in a mechanical sense.. algo’s are active at simultaneously classifying and acting upon that classification..t

so let’s go for a humane label/classification.. ie: daily curiosity

is there such a thing as machine learning for the people..t

ai humanity needs.. augmenting interconnectedness.. listening to every voice everyday and using that data (self-talk as data) to connect us


Dan McQuillan l Losing Your Voice l Meaning 2018 – 15 min – [https://www.youtube.com/watch?v=KtfkCIfgBaw]

1 min – we should ask why we want machines to listen out for signs of distress;
why go to all this trouble when we could do the listening ourselves

can we..? i don’t think we can .. not to every voice.. at least not till we get back in the sync of an undisturbed ecosystem.. so begs a mech to do that.. ie: tech as it could be.. with 2 convers as infra

2 min – machine listening offers the prospect of early intervention.. .beyond anything psychiatry could have previously imagined

but not early/beyond enough if it doesn’t also have a detox embed.. otherwise we’re just listening to ie: whales in sea world

machine learning’s pattern finding.. means it can used for prediction.. as thomas insel says ..digital smoke alarms for people w mental illness

alive people (whales back out of sea world) aren’t predict\able


3 min – ie’s spot depression

that’s too late – today we can listen earlier/deeper

5 min – it’s mathematically impossible to produce all around fairness

indeed.. math ness is one of the cancers to eudaimoniative surplus.. an undisturbed ecosystem.. but today we can have equity (everyone getting a go everyday) ..

there are many diff mathematical ways to define fairness and you can’t satisfy them all at the same time

fairness.. can’t be defined.. always changing et al.. but we can satisfy equity at same time.. in fact.. it won’t work unless it is all at same time

6 min – .. w the net effect of automating ineq

auto ineq

9 min – we need to know how to defend against a therapeutic stasi

no defended ness needed.. if ie: gershenfeld something else law

11 min – seeking to be heard over the stentorian tones of the psychiatric establishment


13 min – what we need is a society where precarity, insecurity and austerity don’t fuel generalised distress..t

hari present in society law

the energy of 7bn alive people in an undisturbed ecosystem

14 min – we should ask instead how our new forms of calculative cleverness
can be stitched into an empathic technics that breaks with machine learning as a mode of targeting..and wreathes computation with ways of caring..t

ie: augmenting interconnectedness via 2 convers as infra


ℳąhą Bąℓi, PhD مها بالي  (@Bali_Maha) tweeted at 10:02 AM on Sun, Jun 09, 2019:
“But we should ask why we want machines to listen out for signs of distress;
Why go to all this trouble when we could do the listening ourselves?” @danmcquillan via @openDemocracy
Cc @KateMfD @14prinsp @Czernie @MiaZamoraPhD @catherinecronin

this article is a transcript (plus some words – and many links) of the 15 min video above – on losing your voice


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paradigm dissident.


After my Ph.D in Experimental Particle Physics I worked with people with learning disabilities and as a mental health advocate, and founded Multikulti, a community-led multilingual website for asylum seekers & refugees. I attended the G8 protest in Genoa in 2001 and was one of 93 people who were beaten, disappeared & tortured by the police. While working at Amnesty International I created the Digital Directorate and led their delegation to the first UN Internet Governance Forum. I co-founded Social Innovation Camp which brought together ideas, people and digital tools to prototype solutions to social problems, and ran camps in different countries including Georgia, Armenia & Kyrgyzstan. More recently I co-founded Science for Change Kosovo, a youth-led air quality citizen science project based on critical pedagogy. I’m currently a Lecturer in Creative & Social Computing