Duplex shows Google failing at ethical and creative AI design

Google CEO Sundar Pichai milked the woos from a clappy, home-turf developer crowd at its I/O conference in Mountain View this week with a demo of an in-the-works voice assistant feature that will e…

A number of venues, including TechCruch have discussed the recent Google demonstration of an intelligent agent Duplex who can make appointments. Many of the stories note how Duplex shows Google failing at ethical and creative AI design. The problem is that the agent didn’t (at least during the demo) identify as a robot. Instead it appeared to deceive the person it was talking to. As the TechCrunch article points out, there is really no good reason to deceive if the purpose is to make an appointment.

What I want to know is what are the ethics of dealing with a robot? Do we need to identify as human to the robot? Do we need to be polite and give them the courtesy that we would a fellow human? Would it be OK for me to hang up as I do on recorded telemarketing calls? Most of us have developed habits of courtesy when dealing with people, including strangers, that the telemarketers take advantage of in their scripts. Will the robots now take advantage of that? Or, to be more precise, will those that use the robots to save their time take advantage of us?

A second question is how Google considers the ethical implications of their research? It is easy to castigate them for this demonstration, but the demonstration tells us nothing about a line of research that has been going on for a while and what processes Google may have in place to check the ethics of what they do. As companies explore the possibilities for AI, how are they to check their ethics in the excitement of achievement?

I should note that Google’s parent Alphabet has apparently dropped the “Don’t be evil” motto from their code of conduct. There has also been news about how a number of employees quit over a Google program to apply machine learning to drone footage for the military.  This is after over 3000 Google employees signed a letter taking issue with the project. See also the Open Letter in Support of Google Employees and Tech Workers that researchers signed. As they say:

We are also deeply concerned about the possible integration of Google’s data on people’s everyday lives with military surveillance data, and its combined application to targeted killing. Google has moved into military work without subjecting itself to public debate or deliberation, either domestically or internationally. While Google regularly decides the future of technology without democratic public engagement, its entry into military technologies casts the problems of private control of information infrastructure into high relief.

 

The Ethics of Datafiction


Information Wants to Be Free, Or Does It? The Ethics of Datafication has just come out in the Electronic Book Review. This article was written with Bettina Berendt at KU Leuven and is about thinking about the ethics of digitization. The article first looks at the cliche phrase “information wants to be free” and then moves on to survey a number of arguments why some things should be digitized.

The Aggregate IQ Files, Part One: How a Political Engineering Firm Exposed Their Code Base

The Research Director for UpGuard, Chris Vickery (@VickerySec) has uncovered code repositories from AggregateIQ, the Canadian company that was building tools for/with SCL and Cambridge Analytica. See The Aggregate IQ Files, Part One: How a Political Engineering Firm Exposed Their Code Base and AggregateIQ Created Cambridge Analytica’s Election Software, and Here’s the Proof from Gizmodo.

The screenshots from the repository show on project called ephemeral with a description “Because there is no such thing as THE TRUTH”. The “Primary Data Storage” of Ephemeral is called “Mamba Jamba”, presumably a joke on “mumbo jumbo” which isn’t a good sign. What is mort interesting is the description (see image above) of the data storage system as “The Database of Truth”. Here is a selection of that description:

The Database of Truth is a database system that integrates, obtains, and normalizes data from disparate sources including starting with the RNC data trust.  … This system will be created to make decisions based upon the data source and quality as to which data constitutes the accepted truth and connect via integrations or API to the source systems to acquire and update this data on a regular basis.

A robust front-end system will be built that allows an authrized user to query the Database of Truth to find data for a particular upcoming project, to see how current the data is, and to take a segment of that data and move it to the Escrow Database System. …

The Database of Truth is the Core source of data for the entire system. …

One wonders if there is a philosophical theory, of sorts, in Ephemeral. A theory where no truth is built on the mumbo jumbo of a database of truth(s).

Ephemeral would seem to be part of Project Ripon, the system that Cambridge Analytica never really delivered to the Cruz campaign. Perhaps the system was so ephemeral that it never worked and therefore the Database of Truth never held THE TRUTH. Ripon might be better called Ripoff.

After the Facebook scandal it’s time to base the digital economy on public v private ownership of data

In a nutshell, instead of letting Facebook get away with charging us for its services or continuing to exploit our data for advertising, we must find a way to get companies like Facebook to pay for accessing our data – conceptualised, for the most part, as something we own in common, not as something we own as individuals.

Evgeny Morozov has a great essay in The Guardian on how After the Facebook scandal it’s time to base the digital economy on public v private ownership of data. He argues that better data protection is not enough. We need to “to articulate a truly decentralised, emancipatory politics, whereby the institutions of the state (from the national to the municipal level) will be deployed to recognise, create, and foster the creation of social rights to data.” In Alberta that may start with a centralized clinical information system called Connect Care managed by the Province. The Province will presumably control access to our data to those researchers and health-care practitioners that commit to using access appropriately. Can we imagine a model where Connect Care is expanded to include social data that we can then control and give others (businesses) access to?

Research Team Security

One of the researchers in the GamerGate Reactions team has created a fabulous set of recommendations for team members doing dangerous research. See Security_Recommendations_2018_v2.0. This document brings together in one place a lot of information and links on how to secure your identity and research. The researcher put this together in support of a panel that I am chairing this afternoon on Risky Research that is part of a day of panels/workshops following the Edward Snowden talk yesterday evening. (You can see my blog entry on Snowden’s talk here.) The key topics covered include:

  • Basic Security Measures
  • Use End-to-End Encryption for Communications  Encrypt Your Computer
  • Destroy All Information
  • Secure Browsing
  • Encrypt all Web Traffic
  • Avoiding Attacks
  • On Preventing Doxing
  • Dealing with Harassment

How Trump Consultants Exploited the Facebook Data of Millions

Cambridge Analytica harvested personal information from a huge swath of the electorate to develop techniques that were later used in the Trump campaign.

The New York Times has just published a story about How Trump Consultants Exploited the Facebook Data of MillionsThe story is about how Cambridge Analytica, the US arm of SCL, a UK company, gathered a massive dataset from Facebook with which to do “psychometric modelling” in order to benefit Trump.

The Guardian has been reporting on Cambridge Analytica for some time – see their Cambridge Analytica Files. The service they are supposed to have provided with this massive dataset was to model types of people and their needs/desires/politics and then help political campaigns, like Trump’s, through microtargeting to influence voters. Using the models a campaign can create content tailored to these psychometrically modelled micro-groups to shift their opinions. (See articles by Paul-Olivier Dehaye about what Cambridge Analytica does and has.)

What is new is that there is a (Canadian) whistleblower from Cambridge Analytica, Christopher Wylie who was willing to talk to the Guardian and others. He is “the data nerd who came in from the cold” and he has a trove of documents that contradict what other said.

The Intercept has a earlier and related story about how Facebook Failed to Protect 30 Million Users From Having Their Data Harvested By Trump Campaign Affiliate. This tells how people were convinced to download a Facebook app that then took your data and that of their friends.

It is difficult to tell how effective the psychometric profiling with data is and if can really be used to sway voters. What is clear, however, is that Facebook is not really protecting their users’ data. To some extent their set up to monetize such psychometric data by convincing those who buy access to the data that you can use it to sway people. The problem is not that it can be done, but that Facebook didn’t get paid for this and are now getting bad press.

Digital Cultures Big Data And Society

Last week I presented a keynote at the Digital Cultures, Big Data and Society conference. (You can seem my conference notes at Digital Cultures Big Data And Society.) The talk I gave was titled “Thinking-Through Big Data in the Humanities” in which I argued that the humanities have the history, skills and responsibility to engage with the topic of big data:

  • First, I outlined how the humanities have a history of dealing with big data. As we all know, ideas have histories, and we in the humanities know how to learn from the genesis of these ideas.
  • Second, I illustrated how we can contribute by learning to read the new genres of documents and tools that characterize big data discourse.
  • And lastly, I turned to the ethics of big data research, especially as it concerns us as we are tempted by the treasures at hand.

Continue reading Digital Cultures Big Data And Society

Are Algorithms Building the New Infrastructure of Racism?

Robert Moses

3quarksdaily, one of the better web sites for extracts of interesting essays, pointed me to this essay on Are Algorithms Building the New Infrastructure of Racism? in Nautilus by Aaron M. Bornstein (Dec. 21, 2017). The article reviews some of the terrain covered by Cathy O’Neil’s book Weapons of Math Destruction, but the article also points out how AIs are becoming infrastructure and infrastructure with bias baked in is very hard to change, like the low bridges that Robert Moses built to make it hard for public transit to make it into certain areas of NYC. Algorithmic decisions that are biased and visible can be studied and corrected. Decisions that get built into infrastructure disappear and get much harder to fix.

a fundamental question in algorithmic fairness is the degree to which algorithms can be made to understand the social and historical context of the data they use …

Just as important is paying attention to the data that is used to train the AIs in the first place. Historic data carries the biases of these generations and they need to be questioned as they get woven into our infrastructure.