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Re-coding Black Mirror, Part II

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We’ll be looking at a couple more papers from the re-coding Black Mirror workshop today:

(If you don’t have ACM Digital Library access, all of the papers in this workshop can be accessed either by following the links above directly from The Morning Paper blog site, or from the WWW 2018 proceedings page).

Pitfalls of affective computing

It’s possible to recognise emotions from a variety of signals including facial expressions, gestures and voices, using wearables or remote sensors, and so on.

In the current paper we envision a future in which such technologies perform with high accuracy and are widespread, so that people’s emotions can typically be seen by others.

Clearly, this could potentially reveal information people do not wish to reveal. Emotions can be leaked through facial micro-expressions and body language making concealment very difficult. It could also weaken social skills if it is believed that there is no need to speak or move to convey emotions. “White lies” might become impossible, removing a person’s responsibility to be compassionate. It could also lead to physical harm:

The ability to quickly detect threats and opportunities via negative or positive emotions could increase the incidence of fighting and violence… for example, a person could feel threatened by seeing their partner and a potential rival feel highly positive emotions toward one another, which could lead to anger and violence.

Misreading emotions, or overly simplifying emotions (e.g. boiling things down to just one emotion to display, rather than the complex mix which is reality), can also cause miscommunications and misunderstandings.

.. if a person’s own inference about someone else’s emotions differs from what is visualized, dissonance and distrust might be felt. Finally, a system could be hacked to make it seem as if a person genuinely feels a different emotion, which could benefit politicians, lawyers, or criminals.

And then of course there’s the possibility that robots and computers, on being able to read emotions, could also gain an advantage in persuading people, perhaps for commercial gain. Think of dark uses such as scams target certain demographics such as the elderly, which can also check that a victim truly believes a story and use emotional feedback to be more convincing.

The authors propose a guideline that “a person’s emotions should only be visualized with their consent, to trusted persons.” It’s going to be hard to defend against systems that quietly observe you though. A person with depression should not be forced to expose their condition to total strangers, and employees should not be afraid of being continually monitored and losing their jobs for some emotional slip-up.

…under privacy regulation such as the GDPR, one’s emotional state could be regarded as personal information and therefore subject to protections and transparencies which are already available today. We believe that such considerations of what problems can occur and how they can be avoided, will enable emotion visualization to contribute positively to people’s well-being.

Ease and ethics of user profiling in Black Mirror

This discussion paper is based on the episode ‘Nosedive’, and examines scenarios in which users are widely profiled, and the profile information becomes embedded in everyday life. (Think of China’s social credit system!). Consider a fictitious organisation F-social that provides services to its users (free or paid) and manages to accumulate a lot of personal information along the way.

A restaurant sends in facial pictures of its customers to F-social to get a metric of the amount of purchasing power they possess and how likely they are to splurge. They are able to do this via a seemingly innocuous notice at their doors that says “by entering the premises you consent to be identified.”

F-social identifies the individuals by looking for matches to their facial profiles in its database of users. If the individual doesn’t use F-social they may still be identifiable in the tagged photos of their friends. If there is really no information, F-social returns the ‘no-match’ result, which is interpreted by the restaurant as being ambiguous and suspicious.

At the next step, F-social computes a score for the restaurant indicating the customer’s likely spending power, and their potential to splurge today. It might do this by looking at past purchases, or obtained via linked financial data. It can see what kinds of dishes have been ordered and their prices. Then F-social looks for indications of any special occasion in the profile – a birthday, anniversary, promotion etc.. Finally F-social considers how far into the salary month the customer is. The experience the customer is about to receive at the restaurant can be heavily influenced by these behind the scenes black-box calculations… “This second-hand effect of limiting access or discriminating based on some metric results in a pressure to conform to accepted behaviours.

The current norm seems to be to consider the practical implications of a technology after its widespread usage and in most cases only when someone else raises objections based on their perceived risks… The core issue underlying the lack of discussions on these topics by technologists (is that) no method for practising ethics integrates into the methodology for work readily enough to adopt it.

To help address this issue, the author’s offer us the ‘Ethics Canvas’, inspired by the popular Business Model Canvas.

The canvas has nine thematic blocks, typically completed in four stages.

  • Identification of stakeholders. Blocks 1 and 2 identify the individuals and group stakeholders based on the technology under consideration.
  • Identification of potential ethical impacts. The next step is to fill in blocks 3,4, 5, and 6 with identified potential ethical impacts for the stakeholders (see questions in the boxes for illustration).
  • Consider ethical impacts on non-stakeholders (boxes 7 and 8 regarding the impact of failures and use of resources).
  • Make an action plan (box 9)

The ethics canvas can be printed or used as a web application that can be used without an account and can be downloaded. Certain features such as collaborative editing, comments, tagging, and persistence are made available through an account. The source of the application is hosted online and is available under the CC-by-SA 3.0 license.

Let’s take a look at how the canvas helps us to analyse our hypothetical F-social restaurant scenario.

Stakeholders

Individual stakeholders include any users of F-social, as well as any non-users tagged in images F-social have access to, and of course customers of the restaurant. Looking at the datasets used by F-social behind the scenes (such as data from credit companies) we can also include users who appear in those datasets as stakeholders.

Affected groups could by any group of people averse to being tracked, e.g. journalists looking for safe places to meet, or people in positions of power where information about their whereabouts can pose a security risk. Any minority group that might inadvertently be disadvantaged by the profiling are also at risk.

Stakeholder impacts

Users may find more incentives to post things that boost their ratings, and refrain from posting negative things. “They are also more likely to provide information if it helps them achieve monetary or other forms of benefits from services that use the ratings to vet customers.” Moreover, if the ratings take into account a user’s social circle, then a user is more likely to want to have their social circle made up of people who will have a positive effect on their rating. Eventually people with higher ratings may look down on those with lower ratings (as we see in the ‘Nosedive’ episode).

For example, places that only cater to people with higher ratings automatically are seen as ‘exclusive’ whereas places that readily accept people with lower ratings might be seen as not being ‘classy’. To a certain extent, this phenomenon is observable today with regards to monetary spending capacity.

Non-stakeholder impacts

The F-social metric may be open to being gamed, or the service attacked or disabled. This could lead to users being denied services. Some clients of the service may try to use it for purposes not deemed acceptable under legal, business, ethical, or moral viewpoints. Governments or state-level entities may demand access to the data.

Mitigating actions?

Assuming the service being provided by F-social is legally acceptable and hence can’t be shutdown on that basis, the authors proposal is to add more transparency: the algorithm used to calculate the rating could be openly evaluated (what if it’s a neural net?) to provide a level of authenticity and oversight to the usage of data, and help prevent false information about the service from spreading. In this section the authors seem to have deviated from (my interpretation of) the intent of box 9, which is that it should be used by the F-social organisation itself to think through its offering before launch, and for continual review. Instead they focus more on what external users who don’t like F-social may be able to ask/force it to do.

You can find out more about the canvas and give it a go for yourself at https://ethicscanvas.org.





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vitormazzi
12 hours ago
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Brasil
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Rules for Teaching

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  1. Be kind: all else is details.
  2. Remember that you are not your learners…
  3. …that most people would rather fail than change…
  4. …and that ninety percent of magic consists of knowing one extra thing.
  5. Never teach alone.
  6. Never hesitate to sacrifice truth for clarity.
  7. Make every mistake a lesson.
  8. Remember that no lesson survives first contact with learners…
  9. …that every lesson is too short from the teacher’s point of view and too long from the learner’s…
  10. …and that nobody will be more excited about the lesson than you are…
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vitormazzi
10 days ago
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Brasil
luizirber
10 days ago
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Davis, CA
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I Will Do Anything to End Homelessness Except Build More Homes

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Homelessness in America has reached crisis levels and I am determined to do everything in my power to fix the problem as long as it doesn’t involve changing zoning laws or my ability to drive alone to work or, well, changing anything, really. I’m more than happy to give a hungry man a sandwich once a year and then brag to my friends about it as long as he doesn’t sit down anywhere in my line of sight to eat it. Same goes for hungry women because I’m also a feminist.

This is so important because everyone should have a bed to sleep in at night and also nothing destroys property values faster than a desperate person on a sidewalk asking for change. I’m not saying I don’t care about human suffering, I just care much, much more about my immediate self-interest because I’m the kind of person who contributes to society by starting companies that leverage technology to build smart tea kettles that brew themselves while you sleep at night. I’m a fucking innovator.

I’m innovating for win-win-whatever solutions where I win, my community wins, and we do whatever to get rid of homelessness. Fixing the problem means lots of things: letters to the editor of my local newspaper, bombastic statements to the press that will make the fruit of my loins cringe for generations, and especially writing vaguely discriminatory, definitely ugly posts on social media about the crisis as it unfolds in my community. Also, I call the police a lot.

Ending homelessness doesn’t mean building more homes because this town is full of homes already, especially mine, which is a single-family mini-mansion on an acre lot that I inherited from my parents and/or managed to purchase with the kind of job and bank terms and economic equality that don’t exist anymore for anyone and only ever really existed for well-educated white Americans. Either that or it’s a magnificent luxury condo with expansive views that I don’t want marred by more luxury condos or — god forbid — affordable housing.

Every room in my Instagram-worthy abode is either filled with clutter or rented out nightly to hipsters from another gentrified, monotone city also suffering from a homelessness crisis — this is a national epidemic, after all. I’m a good person, a generous person, and what made me the person I am is having to work hard for everything my parents gave me, and everything I will, in turn, give to my children.

Listen, I know that the unholy concentration of wealth in America is a big, big, problem, but so is having to constantly say no to people asking for change as I whizz into Whole Foods in my Tesla or Prius (depending on how my startup investments pan out). What’s the point of having all this money if I have to feel bad about it? Also, has anyone actually verified that the homeless people claiming to be veterans aren’t just pulling some elaborate fraud? I’ve never actually met a veteran and I forget for like, decades at a time that the military even exists because the bubble of privilege where I reside is literally impregnable, but I’m suspicious nonetheless.

I know we need more housing, but I was here first and I’m not giving up even one blade of grass on my water-guzzling, pesticide-leaching lawn or a single burner on my twelve-burner Viking range that I never actually use to house another human soul. Tough luck, homeless people. You and your allies can call me names but I won’t hear you over the lushness of my climate-inappropriate rose bushes and the stucco walls I’m paying some desperate immigrant under the table to build for me on the cheap before I low-key call ICE and have them deported.

Look, if you give people homes the next thing you know they’re going to start to get their lives together and then get jobs and start organizing and then they’ll expand Medicare to everyone and build a fucking light rail line instead of a goddamn border wall and no one will drive anymore and cars will die out and the air will get clean and can you imagine the problems we’ll have then?

No. Stop it with the new housing; I’d rather have a homeless crisis.

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jepler
16 days ago
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"Ending homelessness doesn’t mean building more homes because this town is full of homes already, especially mine, which is a single-family mini-mansion on an acre lot that I inherited from my parents and/or managed to purchase with the kind of job and bank terms and economic equality that don’t exist anymore for anyone and only ever really existed for well-educated white Americans. Either that or it’s a magnificent luxury condo with expansive views that I don’t want marred by more luxury condos or — god forbid — affordable housing"
Earth, Sol system, Western spiral arm
vitormazzi
15 days ago
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Brasil
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★ Lobe

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Lobe just launched publicly today:

Lobe is an easy-to-use visual tool that lets you build custom deep learning models, quickly train them, and ship them directly in your app without writing any code. Start by dragging in a folder of training examples from your desktop. Lobe automatically builds you a custom deep learning model and begins training. When you’re done, you can export a trained model and ship it directly in your app.

It’s a completely visual tool from designer Mike Matas and his co-founders Markus Beissinger and Adam Menges. I am always interested in anything Matas does, and Lobe is no exception.

You build and edit Lobe models through a web interface, and there’s a cloud API developers can use for finished models in production. But Lobe also exports to CoreML (for Apple platforms) and TensorFlow. My analogy: writing CoreML by hand is like writing PostScript by hand — possible, but only by a small number of talented experts. Lobe is to CoreML what Illustrator was to PostScript — a profoundly powerful tool that exposes the underlying technology to non-experts through an intuitive visual interface. Lobe looks utterly Matas-ian.

If you have any interest whatsoever in machine learning, drop what you’re doing right now and watch their 13-minute introductory tour. And if you’re not interested in machine learning, watch the video anyway and you’ll become interested in machine learning. It looks that amazing.

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samuel
22 days ago
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Hoooooly moly this demo is incredible. I'm going back to grad school this fall and I plan on taking a handful of machine learning courses and having something like this guide the way is going to be incredible.
The Haight in San Francisco
digdoug
22 days ago
Man, this is great news. Losing Push Pop bugged me. Facebook Paper was the only frontend that treated us better than the ad buyers. I work for a few data scientists these days, and having a tool that fits the way I think will definitely help me career wise. [And let me skip grad school for another decade]
vitormazzi
22 days ago
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Brasil
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Saturday Morning Breakfast Cereal - Clown Humor

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Click here to go see the bonus panel!

Hovertext:
Why do you think they're always smiling?

New comic!
Today's News:
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popular
21 days ago
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vitormazzi
22 days ago
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Brasil
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Saturday Morning Breakfast Cereal - Robins

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Click here to go see the bonus panel!

Hovertext:
Laugh now, but in 50 years this'll be a service you can buy from Alphabet.

New comic!
Today's News:
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popular
28 days ago
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vitormazzi
29 days ago
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Brasil
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1 public comment
fxer
28 days ago
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be sure to read in Bale's voice
Bend, Oregon
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