Category: AI

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Automation as received wisdom

Holly from the UK TV programme Red Dwarf

For your consideration – a Twitter poll in a sponsored tweet from one of the UK’s largest management consultancies.

Why might a management consultancy do this? – To gain superficially interesting yet fatuous data to make quick claims about? Perhaps for the purposes of advertising? Maybe… Perhaps to try to suggest, in a somewhat calculating way, that the company asks the “important” questions about the future and therefore imply they have some answers? Or maybe simply to boost the now-prevailing narrative that automation is widespread, growing and will take your job. Although to be fair to Accenture, that’s not what they ask.

In any case, this is not neutral – though, I recognise it’s a rather minor and perhaps inconsequential example. Nevertheless, it highlights the growth in pushing a narrative of automation from management consultancies, like Accenture, Deloitte and PWC, who are all writing lots of reports suggesting that companies need to be ready for automation.

A cynical analysis would suggest that it’s within the interests of such companies to jump on the narrative – it’s been in the press quite a bit in recent years, then ramp it up, and offer to sell the ‘solutions’.

What I find particularly interesting is that, while newspaper articles parrot the reports from these consultancies, there appears to be (in my digging around) scant serious evidence for this trend. A lot of it is based on economic modelling (of both past and future economic contexts) and some of the reports when they do list methods seem to use adapted versions of models that once said something else.

A case in point is the recent PWC report about automation that claimed up to 30% of UK jobs could be automated by the early 2030s, widely reported in the press (e.g. BBC, Graun, Telegraph), which was based upon a modified (2016) OECD model – the original model suggested that only 9% of jobs in OECD countries were at relatively high risk (greater than 70% risk in their calculation) of automation with the UK rated at just over 10% of jobs.

I’m working my way through this sort of stuff to get at how these sorts of narratives are generated, become received wisdom and feed into a wider form of social imagination about the kinds of socio-economic and technological future we expect. I’m hoping to pull together a book on this theme with the tentative title “The Automative Imagination”.

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The Economist ‘Babbage’ podcast: “Deus Ex Machina”

Glitched still from the film "Her"

An interesting general (non-academic, non-technical) discussion about what “AI” is, what it means culturally and how it is variously thought about. Interesting to reflect on the way ideas about computation, “algorithms”, “intelligence” and so on play out… something that maybe isn’t discussed enough… I like the way the discussion turns around “thinking” and the suggestion of the word “reckoning”. Worth a listen…

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AI Now report

My Cayla Doll

The AI Now Institute have published their second annual report with plenty of interesting things in it. I won’t try and summarise it or offer any analysis (yet). It’s worth a read:

The AI Now Institute, an interdisciplinary research center based at New York University, announced today the publication of its second annual research report. In advance of AI Now’s official launch in November, the 2017 report surveys the current use of AI across core domains, along with the challenges that the rapid introduction of these technologies are presenting. It also provides a set of ten core recommendations to guide future research and accountability mechanisms. The report focuses on key impact areas, including labor and automation, bias and inclusion, rights and liberties, and ethics and governance.

“The field of artificial intelligence is developing rapidly, and promises to help address some of the biggest challenges we face as a society,” said Kate Crawford, cofounder of AI Now and one of the lead authors of the report. “But the reason we founded the AI Now Institute is that we urgently need more research into the real-world implications of the adoption of AI and related technologies in our most sensitive social institutions. People are already being affected by these systems, be it while at school, looking for a job, reading news online, or interacting with the courts. With this report, we’re taking stock of the progress so far and the biggest emerging challenges that can guide our future research on the social implications of AI.”

There’s also a sort of Exec. Summary, a list of “10 Top Recommendations for the AI Field in 2017” on Medium too. Here’s the short version of that:

  1. 1. Core public agencies, such as those responsible for criminal justice, healthcare, welfare, and education (e.g “high stakes” domains) should no longer use ‘black box’ AI and algorithmic systems.
  2. 2. Before releasing an AI system, companies should run rigorous pre-release trials to ensure that they will not amplify biases and errors due to any issues with the training data, algorithms, or other elements of system design.
  3. 3. After releasing an AI system, companies should continue to monitor its use across different contexts and communities.
  4. 4. More research and policy making is needed on the use of AI systems in workplace management and monitoring, including hiring and HR.
  5. 5. Develop standards to track the provenance, development, and use of training datasets throughout their life cycle.
  6. 6. Expand AI bias research and mitigation strategies beyond a narrowly technical approach.
  7. 7. Strong standards for auditing and understanding the use of AI systems “in the wild” are urgently needed.
  8. 8. Companies, universities, conferences and other stakeholders in the AI field should release data on the participation of women, minorities and other marginalized groups within AI research and development.
  9. 9. The AI industry should hire experts from disciplines beyond computer science and engineering and ensure they have decision making power.
  10. 10. Ethical codes meant to steer the AI field should be accompanied by strong oversight and accountability mechanisms.

Which sort of reads, to me, as: “There should be more social scientists involved” 🙂

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Brian Cox, cyberpunk

Man with a colander on his head attached to electrodes

Doing public comms of science is hard, and it’s good to have people trying to make things accessible and good to excite and interest people about finding things out about the world… but it can tip over into being daft pretty easily.

Here’s the great D:ream-er Brian Cox going all cyberpunk on brain/mind uploads… (note the lad raising his eyes to the ceiling at 0:44 🙂 )

This made me wonder how Hubert Dreyfus would attempt to dispel the d:ream (don’t all groan at once!) as the ‘simulation of brains/minds’ is precisely the version of AI that Dreyfus was critiquing in the 1970s. If you’re interested in further discussion of ‘mind uploading’, and not my flippant remarks, see John Danaher’s writing on this on his excellent blog.

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AI Now post-doc positions

Holly from the UK TV programme Red Dwarf

This looks like a great opportunity for someone interested in the sorts of things the “AI Now” Institute (NYU) does. Link.

AI Now is looking for two to three postdoctoral researchers whose work resonates with the Institute’s mission. This position is an ideal opportunity for scholars who are interested in understanding the growing role of AI and related technologies within social and political institutions, and who are excited by the idea of shaping a new and far-ranging research field.

ABOUT THE AI NOW INSTITUTE

The AI Now Institute at New York University is an interdisciplinary community researching the social and economic implications of artificial intelligence and related algorithmic systems. We focus on producing foundational research illuminating the social contexts as automated decision-making moves deeper into core institutions like health, education, and criminal justice.

Founded in 2017 by Kate Crawford and Meredith Whittaker, AI Now is housed at NYU, where it fosters vibrant interdisciplinary engagement across the University and beyond. AI Now’s current partners at NYU include: the Tandon School of Engineering, the Steinhardt School of Culture, Education, and Human Development, the Law School, the Stern School of Business, and the Center for Data Science.

AI NOW POSTDOCTORAL FELLOWSHIPS

As an interdisciplinary institute at NYU, AI Now will provide postdocs with the opportunity to develop their scholarship at a top academic institution with an explicit remit to collaborate with researchers and practitioners across different fields, whether in NYU, at partner institutions, or within relevant industry and civil society organizations. AI Now has a strong network across these sectors, and will make this network available to postdocs where relevant and useful.

Postdocs will devote time to their own research and collaborative projects and will contribute to AI Now programs and events related to their research portfolio. Teaching is not expected, but may be an option, depending on a candidate’s availability and interest.

AI Now is committed to mentorship and support and to accommodating and resourcing research agendas that fit within its core mission. Postdocs will become a core part of a growing research community that includes reading groups, expert workshops, international conferences, regular salons, and site-specific travel. Fellows will also have the opportunity to help shape the annual AI Now Symposium.

RESOURCES AND BENEFITS

  • Competitive salary and benefits
  • Access to an exceptional network of mentors and established researchers spanning NYU and beyond, including civil society and industry practitioners
  • A generous research stipend for conferences (including international), fieldwork, and research materials, available as needed
  • Relocation assistance available as needed

See the full text of the call here.

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Reblog> Idols of Silicon and Data

Deep Thought, Hitchhikers Guide to the Galaxy

From LM Sacasas:

Idols of Silicon and Data

In 2015, former Google and Uber engineer, Anthony Levandowski, founded a nonprofit called Way of the Future in order to develop an AI god and promote its worship. The mission statement reads as follows: “To develop and promote the realization of a Godhead based on artificial intelligence and through understanding and worship of the Godhead contribute to the betterment of society.”

A few loosely interconnected observations follow.

Read the full post.

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“Invisible Images: Ethics of Autonomous Vision Systems” Trevor Paglen at “AI Now” (video)

racist facial recognition

Via Data & Society / AI Now.

Trevor Paglen on ‘autonomous hypernormal mega-meta-realism’ (probably a nod to Curtis there). An entertaining brief talk about ‘AI’ visual recognition systems and their aesthetics.

(I don’t normally hold with laughing at your own gags but Paglen says some interesting things here – expanded upon in this piece (‘Invisible Images: Your pictures are looking at you’) and this artwork – Sight Machines [see below]).

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19 ‘AI’-related links

Twiki the robot from Buck Rogers

Here’s some links from various sources on what “AI” may or may not mean and what sorts of questions that prompts… If I was productive, not sleep-deprived (if… if… etc. etc.) I’d write something about this, but instead I’m just posting links.

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The “Ethics and Governance of Artificial Intelligence Fund” commits $7.6M to research “AI for the public interest”

A press release from the Knight Foundation and another from Omidyar Network highlight their joint effort with several other funders to commit $7.6M to be distributed across several international institutions to research “AI for the public interest”. This seems like an ambitious and interesting research programme, albeit located in the elite institutions one might unfortunately expect to hoover up this sort of funding… Nevertheless, it will be interesting to see what comes of this.

Here’s some snippets (see the full Knight Foundation PR here and the Omidyar PR here).

…a $27 million fund to apply the humanities, the social sciences and other disciplines to the development of AI.

The MIT Media Lab and the Berkman Klein Center for Internet & Society at Harvard University will serve as founding academic institutions for the initiative, which will be named the Ethics and Governance of Artificial Intelligence Fund. The fund will support a cross-section of AI ethics and governance projects and activities, both in the United States and internationally.

…

The fund seeks to advance AI in the public interest by including the broadest set of voices in discussions and projects addressing the human impacts of AI. Among the issues the fund might address:

  • Communicating complexity: How do we best communicate, through words and processes, the nuances of a complex field like AI?
  • Ethical design: How do we build and design technologies that consider ethical frameworks and moral values as central features of technological innovation?
  • Advancing accountable and fair AI: What kinds of controls do we need to minimize AI’s potential harm to society and maximize its benefits?
  • Innovation in the public interest: How do we maintain the ability of engineers and entrepreneurs to innovate, create and profit, while ensuring that society is informed and that the work integrates public interest perspectives?
  • Expanding the table: How do we grow the field to ensure that a range of constituencies are involved with building the tools and analyzing social impact?

…

Supporting a Global Conversation

  • Digital Asia Hub (Hong Kong): Digital Asia Hub will investigate and shape the response to important, emerging questions regarding the safe and ethical use of artificial intelligence to promote social good in Asia and contribute to building the fund’s presence in the region. Efforts will include workshops and case studies that will explore the cultural, economic and political forces uniquely influencing the development of the technology in Asia.
  • ITS Rio (Rio de Janeiro, Brazil): ITS Rio will translate international debates on artificial intelligence and launch a series of projects addressing how artificial intelligence is being developed in Brazil and in Latin America more generally. On behalf of the Global Network of Internet and Society Research Center, ITS Rio and the Berkman Klein Center will also co-host a symposium on artificial intelligence and inclusion in Rio de Janeiro, bringing together almost 80 centers and an international set of participants to address diversity in technologies driven by artificial intelligence, and the opportunities and challenges posed by it around the world.

Tackling Concrete Challenges

  • AI Now (New York): AI Now will undertake interdisciplinary, empirical research examining the integration of artificial intelligence into existing critical infrastructures, looking specifically at bias, data collection, and healthcare.
  • Leverhulme Centre for the Future of Intelligence (Cambridge, United Kingdom): Leverhulme Centre for the Future of Intelligence will be focused on bringing together technical and legal perspectives to address interpretability, a topic made urgent by the European Union’s General Data Protection Regulation coming into force next year.
  • Access Now (Brussels, Belgium): Access Now will contribute to the rollout of the General Data Protection Regulation by working closely with data protection authorities to develop practical guidelines that protect user rights, and educate public and private authorities about rights relating to explainability. The organization will also conduct case studies on data protection issues relating to algorithms and artificial intelligence in France and Hungary.

Bolstering Interdisciplinary Work 

  • FAT ML (Global): FAT ML will host a researcher conference focused on developing concrete, technical approaches to securing values of fairness, accountability, and transparency in machine learning.
  • Data & Society (New York): Data & Society will conduct a series of ethnographically-informed studies of intelligent systems in which human labor plays an integral part, and will explore how and why the constitutive human elements of artificial intelligence are often obscured or rendered invisible. The research will produce empirical work examining these dynamics in order to facilitate the creation of effective regulation and ethical design considerations across domains.

##

About the Ethics and Governance of Artificial Intelligence Fund 

The Ethics and Governance of Artificial Intelligence Fund aims to support work around the world that advances the development of ethical artificial intelligence in the public interest, with an emphasis on applied research and education. The fund was launched in January 2017, with an initial investment of $27 million from the John S. and James L. Knight Foundation, Omidyar Network, LinkedIn founder Reid Hoffman, the Hewlett Foundation, and Jim Pallotta. The activities supported through the fund aim to address the global challenges of artificial intelligence from a multidisciplinary perspective–grounded in data, code, and academic analysis. The fund will advance the public understanding of artificial intelligence and support the creation of networks that span disciplines and topics related to artificial intelligence. The Miami Foundation is serving as fiscal sponsor for the fund.

Via Alexis Madrigral.

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The history of the future of automation – lessons from ed tech

Automated taxi figure in the 1990 film Total Recall

I’ve been re-reading the excellent essay by Audrey Watters: Driverless Ed-Tech: The history of the future of automation in education. I really recommend reading it!

Following on from the vague points I made in my last post about an automative imaginary – one way of getting at this is a sort of classic (political economy) critique, which Watters very adroitly takes in relation to ed-tech and MOOCs (etc), and which she write really clearly – so, here is snippet:

“Put me out of a job.” “Put you out of a job.” “Put us all out of work.” We hear that a lot, with varying levels of glee and callousness and concern. “Robots are coming for your job.”

We hear it all the time. To be fair, of course, we have heard it, with varying frequency and urgency, for about 100 years now. “Robots are coming for your job.” And this time – this time – it’s for real.

I want to suggest – and not just because there are flaws with Uber’s autonomous vehicles (and there was just a crash of a test vehicle in Arizona last Friday) – that this is not entirely a technological proclamation. Robots don’t do anything they’re not programmed to do. They don’t have autonomy or agency or aspirations. Robots don’t just roll into the human resources department on their own accord, ready to outperform others. Robots don’t apply for jobs. Robots don’t “come for jobs.” Rather, business owners opt to automate rather than employ people. In other words, this refrain that “robots are coming for your job” is not so much a reflection of some tremendous breakthrough (or potential breakthrough) in automation, let alone artificial intelligence. Rather, it’s a proclamation about profits and politics. It’s a proclamation about labor and capital.

More specific to education, Watters highlights the logic offer by Udacity, one of the big MOOC start-ups:

“We want to be the Uber of education,” Thrun told The Financial Times, which added that, “Mr Thrun knows what he doesn’t want for his company: professors in tenure, which he claims limits the ability to react to market demands.”

In other words, “disrupt” job protections through a cheap, precarious labor force doing piecemeal work until the algorithms are sophisticated enough to perform those tasks. Universities have already taken plenty of steps towards this end, without the help of algorithms or for-profit software providers. But universities are still bound by accreditation (and by tradition). “Anyone can teach” is not a stance on labor and credentialing that many universities are ready to take.

[read all of Watters’ argument here.]

One of the areas in which what I’ve called the automative imaginary/imagination overlaps with wider stories about digital tech disruption and the widespread creed of that disruption being normatively good, if not admirable, is where automation overlaps with the ‘gig economy’. As we can see, via Thrun, one of the models in play here is not to ‘destroy’ jobs but rather to decouple them from some of the elements that make them valuable and either reallocate or automate those and then offer the remaining tasks as precarious work – which you have to sign up for through a proprietary system as a contractor, rather than an employee.

The ways we are invited to see ‘automation’ by some are over-coded with strong narratives of ‘disruption’ and the breaking down of established employment rights into a two their system in which the ‘taskers’ (as Guy Standing calls them) take the precarious work for relatively meagre earnings and the tech company owners and a few they bring along with them hoover up the profits.

An alternative to such narratives might be ‘accelerationism‘ but I remain skeptical at present (but I’ve not read enough to form an opinion really). It seems to me, we (geographers, social scientists, citizens?! … well, me anyway!) really do need to talk and think about work.