2016-12-09

Plenary #ifipwg82 Karin Knorr-Cetina, Keynote IFIP WG 8.2 Working Conference, Dublin 2016

Introduction by Séamas Kelly, The Centre for Innovation, Technology & Organisation, University College Dublin

This digest was created in real-time during the meeting, based on the speaker’s presentation(s) and comments from the audience. The content should not be viewed as an official transcript of the meeting, but only as an interpretation by a single individual. Lapses, grammatical errors, and typing mistakes may not have been corrected. Questions about content should be directed to the originator. The digest has been made available for purposes of scholarship, by David Ing.

Welcoming Karin Knorr-Cetina, U. Chicago, Otto Borchert Distinguished Service Professor, Departments of Sociology and Anthropology

Science and Technology Studies

Post-social relations, to broaden social inquiry, relations with objects as well as other human beings:  interobjectivity

[Karin Knorr-Cetina]

Title has changed from “What If the Screens Went Black? The Coming of Software Agents”, published in the proceedings at http://dx.doi.org/10.1007/978-3-319-49733-4_1

First time to Dublin

Home country of Austria

Will talk about work on finance

3 technological transitions in finance:  good this is a working conference, will discuss, they’re not finished

Developing a technosphere, looking a performance level, how is technology used

1. A form of temporalization: A new ontology, fluid and liquid

2. From technology to media

3. Scaled up social form with meta-actors

Interest in exchange markets

Concentrations in market:  UK, U.S. Japan

Over the counter market:  huge, foreign exchange between banks

Not regulated much, done in exchanges

Technology is trading screens

1. Streamers 1886-1980s

2. Scopes 1980s

3. Algorithms 2000s

Original stock ticker: cross between printer and telegraph

Connected exchanges

Not related to foreign exchange, but stock markets

Name of security, price change time, transaction time

People then had the market on tape

Before calling, wanted to know who was trading what at what price

Transcript from Knorr & Preda 2007, from the days in which ticker tape was still used

Saw price differentials

First transition to ticker tape had consequences over 10 to 15 years

Beginning regime of attention, so could know what was going on

Expanding information boundaries, could see not only what was happening in New York, then Boston, then London — a telegraph

Origin of a new community of practice related to ticker tape, today called technical analysts — looking at numbers from tape, and then ordering them differently, e.g. price differentials over time, volumes

New social stratification around ticket possession:  in-group tried to prevent out-group from getting ticker tape

Ticker tape created a sequential time

Taking manifested in trading in market, temporalization of market

Changed with computer screens, 100 years later

Face to screen

On screen, more than price

Market world on screen:  if it’s not on the screen, it doesn’t exist, e.g. 9/11 was on screen quickly

Scopic media:  screen-based technologies

First Reuters Monitor, 1973

1981 action capability, could trade through the screen, didn’t need phone, went live to 145 institutions in 9 countries

At 2012:  400,000 Thomson-Reuters terminals; 315,000 Bloomberg terminals world

Had put big sheets on floors, with prices written manually

Scoping mechanism:

Instant visible making of the market that is reflexive

Watch the market on screen, but also trade, which changes what you watch

Augments:  offers analysis, information, news about what’s going on, referential whole in a Heideggerian sense, to the audience

Audience responds to projected reality on screen, rather the pre-reflected (e.g. phone calls)

Why “media”?

Always an audience

Can analyze as dramaturgical

Analytical staging of the market

Transition to scopes:  from piping to beaming

Piping:  social relation based (networks), maintain relationships over the telephone

Beaming:  tele-coordination

Despite underwater pipes (networking), performance isn’t a network anymore, as everyone sees the same screen

Tele-coordination: When you scan scope it, you don’t have to network it!

Market always has an audience

Neuro-market synchronization

Neuro-physiological level

Asked traders how they trade, not getting an answer:  seat of pants, know what to do (which doesn’t explain anything to a social scientists)

Social science says something about implicit knowledge, but it’s not science

Neuro-physiology not yet a science:  have pre-frontal (explicit, accessible to conscioius); implicit (is skill based, content not verbalizable, inaccessible to conscious awareness)

Two performance systems recruit and develop different cognitive circuits

Can develop pre-frontal explicit

But in market where have to respond in seconds to market changes, rely on implicit so no delays in sequence, but more traders are integrated into the scopic system

Implicit cognitive processes, can’t do by thinking, have to act

Results in a regime of attention, traders have to watch the market

System between trader and screen is false:  implicit processing to the neural level

Master skiers say “You can’t win a thing with thinking”

Based on implicit processing

Explicit system is capacity limited, processing 4 to 6 variables at the same time

Making a serve in tennis takes more than 4 to 6 things

Also, it’s sequential

Get a neuro-market synchronization

Global

Everyone watching the same screen, at an implicit level

Traders give indications of that:  don’t know how to trade

Ethnography, staying at distance doesn’t work

More like a tiger watching a prey, ready to jump

Feels like a physical connectedness

When the market turns against them, they feel as if they’re sexually violated, e.g. I got shafted, I got hammered

Not a psychic level, it’s emotional

Given neuro connection, maximum implicitness has negative aspects:

Task subtractions:  doesn’t see the market

Implications are subtracted

Content subtracted

Social-moral subtraction

Inability of Wall Street to understand

Second transition:  unified global market, 1980s-2005

Interbank trading, complete

Streaming market in analytic time

Analytic and differential time:  time flow, have to get into this

Ontology of the real is slowing

Continuation of temporalization in speed:  schedules, regime of attention physiological

Moving from screens to servers watching algorithms

Subterranean action of algorithms

Now observe spiking, e.g. NYSE isn’t now dominant — from 2004 80%

Rise of algorithms that trade

A major disruption

Temporalization of social world, could be at its limits in terms of speed, as at speed of light

Vocabulary changes:  low latency, speed trading

Also thinking about infrastructure at speed of light

Fibre optical cable can go to 2/3 of speed of light, but microwave can get to 99%

Microwave connections (New York to L.A.) compared to fibre optic (to Japan) will gain 4 to 5 seconds

Described by Michael Lewis in Flash Boys, between Chicago and New York

Change in practice

Trading rooms use to be communications rooms (although they were through screen)

Constant talking, now not so much

Trading rooms are mostly silent

Competing on speed, rather than trading strategy

South Korea is creating barriers to increase speed further, goes back to trading strategy over speed

Humans disappear

Proprietary trading farms, as opposed to doing on public trading floor with big banks

Firms have become traders

Question on integration of non-human actions into the social world

Luckmann 20 years ago:  why does the social world always have to be near to human being?  It’s not necessary

Are we integrating algorithms into the social world?

Professional changes:

Desks become firms

Drastically reduced number of skilled traders, rest done by algorithms

Influx of quants (math, stats, physics)

New educational requirements on remaining human traders (who used to be apprentices in banks for 2 years before becoming assisting traders, now they need a university degree with sophisticated math)

Algorithms:

Instructions to accomplish a task

Also are programs to act:  e.g. learning algorithm might have models implemented in the algorithm

Algorithm can then be a trader:  assistant to human traders (in simple transactions)

Strategic counterpart into human beings, could become dominant market actor

There are firms where only algorithms change

May have to reconceptualize markets

Infrapersons:

From the technical literature on what algorithms do

Algorithm as unemotional as seen as one of best features

Algorithm may be scientific; global

Human actors have use discipline to rein in emotions

Algorithms are dumb, don’t need discipline

Human being self-regulation with moral judgement; software agents regulate via risk assessment

Algorithms are fast, unlike human beings

Develops algorithmic culture of time

Leads to flash crashes

First flash crash of May 10, 2010 (unresolved today), market crashed

Dow down 1000 points before recovering, $1 million value erase

All happened within 13 minutes, then recovering in 26 minutes to normal orderly

Stop of the market was due to a breakdown of technology:  correct market prices weren’t being displayed, even though trading could happen

Have had many flash crashes:

Nobody really loses

Rebounds as quick as failing (as the market speaks)

Liquidity refreshed

October 2016, GBP mysterious crash, no explanation

2010 crash could be explained by aggregate data, done by SEC

Nothing economically intersting happens, just have to stick it out

If don’t panic, get excess turbulence, and then recovery

Is this an economic ritual?

Goffman says rituals are symbolic representations of social order

Symbolic representations of social order

Flash crash doesn’t cast a shadow

This is beyond interpretation

Economic ritualization

Market could create synthetic persons, at speed of light

Still holds up

Crashes don’t bring the market down, crashes increase solidarity with the market

Scaling the market?

Crashes could bring in a phenomenological others, encountered as an actor

Not like an automatic car (which is more a tool)

Economic ritualization have financial markets emerge from change

Conceptualization:  institutions versus markets, market isn’t a hierarchy, it’s flat social form, no CEO or governance structure

Trading use to have an interactional moral level

In addition to infrapersons, have metapersons (an in between category)

CEO level is not involved in trading

Trading floor not managed from above

Traders aren’t watching trades, they’re managing and changing algorithms (at least every 3 months)

Traders aren’t called traders any more, meta-person not doing the activity

Involved in advanced cognitive:  math skills, combined with engineering skills

If have meta-persons, market is no longer a flat transactional form

It has levels

Traders become an epistemic class

Beyond knowledge society, based on theoretical knowledge (Daniel Bell)

Epistemic class of sophisticated math with agency engineering and money making

Used to be acephalous social form without a master, but now masters have matured (and breed)

Knowledge society is pushing itself through, not just technical analysts, but watching and changing algorithms

Summary:

Talked about 3 disruptive stages

Looked a performative view of technology:  temporalization, mediatization, rescaling of social form

Rescaling of social form into two levels:  meso level on market; rise of hybrid epistemic class

[Comments by Hugh Wilmott]

Screen went black an hour ago, because the talk changed

Conference theme:  shift from what technology means, to socio-technological appendices do

Examining in context of financial markets

Financial markets have been under-researched, except for people in financial economics

Few in organizational studies have researched

Some change, due to financial crisis

Important, we rely on those markets

Applications of technologies are at the cutting edge

Position with socio-technical systems to post-WWII period, could re-engage

Think of issues of power and class

Coal mining studies of early 1950s

Emerging hybrid epistemic class

Pre-reflexive interaction

Tends to be lost in second phase, step in scoping phase

Informal networks become less significant, relying more and more on data on screen

Characterization as network doesn’t work

Implicit processing system

Traders like skiing

Being a physical activity, like sexual assault when the market turns against the trader

Situated learning could be important

Embodied awareness present in the practice

Question about algorithms, which has become important to trading practice

Can we attribute agency to trading algorithms?

Caution against treating algorithms as agents

What kind of attributions do traders make about algorithms, and the fantasies they make, leading to performative effects?

Exploration of hybrid people:

People who have an understanding of algorithm, and of market

Speed was important, now it’s the hybridity, insight into the design of the algorithms

Competitive advantage in recruiting and developing people with the hybrid capabilities

People who develop and acquire hybrid capabilities can move away from banks, to independence

Changes structure of the market

Legal context:

Regulation of activities

Issues of corporate governance and public accountability

Future research agenda on regulatory effects, where regulators are not capable of catching up

[Questions]

Bad day for market analysts.  Philosophical changes.  Are we controlled by algorithms?

Spoke to a metaperson about how to debug algorithms?  They change them all of the time, they don’t have time to really debug them?

Choice of wording to catch phenomena?  What metapersons?

Do algorithms have emotions?  They have rituals?  Flash crashes

Collective agency?

Systems drift?

Flash crashes, no shadow?

[Responses by Karin]

Being controlled by algorithms

In some areas, could be worse than in financial markets

e.g. what will self-driving cars do to the male ego?

Maybe not control, but a shift that could have identity consequences

Economists admit it’s an open question

Automation could be different from the steam engine

If we don’t create new jobs, could create new social problems

Consequences are not discussed

In financial market, needs to be control of the algorithms

Flash crashes don’t give up control, they do suggest excess trading that human beings can’t handle, but the financial system does

Meta-persons

No time for debugging

Answer may be short

Firms using algorithms have an interest in debugging, because there could be immediate costs

Could be interested in constructing algorithms so that they don’t do too much damage in one go

Regulators:  sane, or cognitively captured?

Regulating from the outside:  could create more problems

Luhmann:  I touch it, but I touch it with a lot of care

10 years of changes in language:

Trying to stay with usual languages or professionalization doesn’t capture fantasies

After studying physicists and molecular biologists, thought financial markets should be simpler, but it’s not true

The epistemology of markets isn’t the same as epistemology of natural sciences

Rating agencies and analysts are paid by institutions, which creates contamination:  Chinese walls don’t really work

Economics and financial progress works

Different language for meta-persons

In native languages, spirits are part of the world

Polity in tribes that don’t have a governance system

A market is supposed to egalitarian, but now has a governance structure

Call it a metapersons, not CEOs

Can’t use hierarchies and markets

Trying to incorporate phenomenology

Do algorithms have emotions?

No

It’s not the algorithms that have rituals

A ritual has solidarity consequences, in the social sciences (Durkheim, Goffman, interaction-ritual-chains)

Not really changing, it’s a symbolic consequence

Increased solidarity, increased identification

Question as sociologist:  do we need to integrate algorithms into our sociological notions?

Algorithms bring markets down, but then don’t bring the market down

Governments have dignified the algorithms

Collective agency could be a topic of investigation (not done here)

They’re going to take our jobs, in professionals areas (law, teaching)

Will be a collective effect of algorithms that will affect the social world

Do algorithms shift?

There are learning algorithms

They learn not by what they’re supposed to learn, they respond to the data

A recent development

Flash crashes not financially relevant, but socially relevant

Not a real ritual, would be symbolic

Market is brought down, not just a symbol

Social effects of making algorithms more acceptable

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