Tag: ethics

Microcast #078 — Values-based organisations

I’ve decided to post these microcasts, which I previously made available only through Patreon, here instead.

Microcasts focus on what I’ve been up to and thinking about, and also provide a way to answer questions from supporters and other readers/listeners!

This microcast covers ethics in decision-making for technology companies and (related!) some recent purchases I’ve made.

Show notes

Friday floutings

Did you see these things this week? I did, and thought they were aces.

  1. Do you live in a ‘soft city’? Here’s why you probably want to (Fast Company) — “The benefits of taking a layered approach to building design—and urban planning overall—is that it also cuts down on the amount of travel by car that people need to do. If resources are assembled in a way that a person leaving their home can access everything they need by walking, biking, or taking transit, it frees up space for streets to also be layered to support these different modes.”
  2. YouTube should stop recommending garbage videos to users (Ars Technica) — “When a video finishes playing, YouTube should show the next video in the same channel. Or maybe it could show users a video selected from a list of high-quality videos curated by human YouTube employees. But the current approach—in which an algorithm tries to recommend the most engaging videos without worrying about whether they’re any good—has got to go.”
  3. Fairphone 3 is the ‘ethical’ smartphone you might actually buy (Engadget) — “Doing the right thing is often framed as giving up something. You’re not enjoying a vegetarian burger, you’re being denied the delights of red meat. But what if the ethical, moral, right choice was also the tastiest one? What if the smartphone made by the yurt-dwelling moralists was also good-looking, inexpensive and useful? That’s the question the Fairphone 3 poses.”
  4. Uh-oh: Silicon Valley is building a Chinese-style social credit system (Fast Company) — “The most disturbing attribute of a social credit system is not that it’s invasive, but that it’s extralegal. Crimes are punished outside the legal system, which means no presumption of innocence, no legal representation, no judge, no jury, and often no appeal. In other words, it’s an alternative legal system where the accused have fewer rights.”
  5. The Adults In The Room (Deadspin) — “The tragedy of digital media isn’t that it’s run by ruthless, profiteering guys in ill-fitting suits; it’s that the people posing as the experts know less about how to make money than their employees, to whom they won’t listen.”
  6. A brief introduction to learning agility (Opensource.com) — “One crucial element of adaptability is learning agility. It is the capacity for adapting to situations and applying knowledge from prior experience—even when you don’t know what to do. In short, it’s a willingness to learn from all your experiences and then apply that knowledge to tackle new challenges in new situations.”
  7. Telegram Pushes Ahead With Plans for ‘Gram’ Cryptocurrency (The New York Times) — “In its sales pitch for the Gram, which was viewed by The New York Times, Telegram has said the new digital money will operate with a decentralized structure similar to Bitcoin, which could make it easier to skirt government regulations.”
  8. Don’t Teach Tools (Assorted Stuff) — “As Culatta notes, concentrating on specific products also locks teachers (and, by extension, their students) into a particular brand, to the advantage of the company, rather than helping them understand the broader concepts of using computing devices as learning and creative tools.”
  9. Stoic Reflections From The Gym (part 2) by Greg Sadler (Modern Stoicism) — “From a Stoic perspective, what we do or don’t make time for, particularly in relation to other things, reflects what Epictetus would call the price we actually place upon those things, on what we take to be goods or values, evils or disvalues, and the relative rankings of those in relation to each other.”

Calvin & Hobbes cartoon found via a recent post on tenpencemore

The drawbacks of Artificial Intelligence

It’s really interesting to do philosophical thought experiments with kids. For example, the trolley problem, a staple of undergradate Philosophy courses, is also accessible to children from a fairly young age.

You see a runaway trolley moving toward five tied-up (or otherwise incapacitated) people lying on the tracks. You are standing next to a lever that controls a switch. If you pull the lever, the trolley will be redirected onto a side track, and the five people on the main track will be saved. However, there is a single person lying on the side track. You have two options:

  1. Do nothing and allow the trolley to kill the five people on the main track.
  2. Pull the lever, diverting the trolley onto the side track where it will kill one person.

Which is the more ethical option?

With the advent of autonomous vehicles, these are no longer idle questions. The vehicles, which have to make split-second decision, may have to decide whether to hit a pram containing a baby, or swerve and hit a couple of pensioners. Due to cultural differences, even that’s not something that can be easily programmed, as the diagram below demonstrates.

Self-driving cards: pedestrians vs passengers

For two countries that are so close together, it’s really interesting that Japan and China are on the opposite ends of the spectrum when it comes to saving passengers or pedestrians!

The authors of the paper cited in the article are careful to point out that countries shouldn’t simply create laws based on popular opinion:

Edmond Awad, an author of the paper, brought up the social status comparison as an example. “It seems concerning that people found it okay to a significant degree to spare higher status over lower status,” he said. “It’s important to say, ‘Hey, we could quantify that’ instead of saying, ‘Oh, maybe we should use that.’” The results, he said, should be used by industry and government as a foundation for understanding how the public would react to the ethics of different design and policy decisions.

This is why we need more people with a background in the Humanities in tech, and be having a real conversation about ethics and AI.

Of course, that’s easier said than done, particularly when those companies who are in a position to make significant strides in this regard have near-monopolies in their field and are pulling in eye-watering amounts of money. A recent example of this, where Google convened an AI ethics committee was attacked as a smokescreen:

Academic Ben Wagner says tech’s enthusiasm for ethics paraphernalia is just “ethics washing,” a strategy to avoid government regulation. When researchers uncover new ways for technology to harm marginalized groups or infringe on civil liberties, tech companies can point to their boards and charters and say, “Look, we’re doing something.” It deflects criticism, and because the boards lack any power, it means the companies don’t change.

 […]

“It’s not that people are against governance bodies, but we have no transparency into how they’re built,” [Rumman] Chowdhury [a data scientist and lead for responsible AI at management consultancy Accenture] tells The Verge. With regard to Google’s most recent board, she says, “This board cannot make changes, it can just make suggestions. They can’t talk about it with the public. So what oversight capabilities do they have?”

As we saw around privacy, it takes a trusted multi-national body like the European Union to create a regulatory framework like GDPR for these issues. Thankfully, they’ve started that process by releasing guidelines containing seven requirements to create trustworthy AI:

  1. Human agency and oversight: AI systems should enable equitable societies by supporting human agency and fundamental rights, and not decrease, limit or misguide human autonomy.
  2. Robustness and safety: Trustworthy AI requires algorithms to be secure, reliable and robust enough to deal with errors or inconsistencies during all life cycle phases of AI systems.
  3. Privacy and data governance: Citizens should have full control over their own data, while data concerning them will not be used to harm or discriminate against them.
  4. Transparency: The traceability of AI systems should be ensured.
  5. Diversity, non-discrimination and fairness: AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility.
  6. Societal and environmental well-being: AI systems should be used to enhance positive social change and enhance sustainability and ecological responsibility.
  7. Accountability: Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes.

The problem isn’t that people are going out of their way to build malevolent systems to rob us of our humanity. As usual, bad things happen because of more mundane requirements. For example, The Guardian has recently reported on concerns around predictive policing and hospitals using AI to predict everything from no-shows to risk of illness.

When we throw facial recognition into the mix, things get particularly scary. It’s all very well for Taylor Swift to use this technology to identify stalkers at her concerts, but given its massive drawbacks, perhaps we should restrict facial recognition somehow?

Human bias can seep into AI systems. Amazon abandoned a recruiting algorithm after it was shown to favor men’s resumes over women’s; researchers concluded an algorithm used in courtroom sentencing was more lenient to white people than to black people; a study found that mortgage algorithms discriminate against Latino and African American borrowers.

Facial recognition might be a cool way to unlock your phone, but the kind of micro-expressions that made for great television in the series Lie to Me is now easily exploited in what is expected to become a $20bn industry.

The difficult thing with all of this is that it’s very difficult for us as individuals to make a difference here. The problem needs to be tackled at a much higher level, as with GDPR. That will take time, and meanwhile the use of AI is exploding. Be careful out there.


Also check out:

Assassination markets now available on the blockchain

I first mentioned so-called ‘assassination markets’ in one of my weeknotes back in 2015 when reporting back on a dinner party conversation. For those unfamiliar, the idea has been around for at least the last twenty years.

Here’s how Wikipedia defines them:

An assassination market is a prediction market where any party can place a bet (using anonymous electronic money and pseudonymous remailers) on the date of death of a given individual, and collect a payoff if they “guess” the date accurately. This would incentivise assassination of individuals because the assassin, knowing when the action would take place, could profit by making an accurate bet on the time of the subject’s death. Because the payoff is for accurately picking the date rather than performing the action of the assassin, it is substantially more difficult to assign criminal liability for the assassination.

Of course, the blockchain is a trustless system, so perfect for this kind of thing. A new platform called Augur is a prediction market and so, of course, one of the first things that appears on there are ‘predictions’ about the death of Donald Trump in 2018:

Everyone knew that it was inevitable that assassination markets would quickly pop up on decentralized prediction market platform Augur, but that doesn’t make the fact that users are now betting on whether U.S. President Donald Trump will be assassinated by the end of the year any less jarring.

Yet this market exists, and, though not the most popular bet on Augur, more than 50 shares have been traded on it as of the time of writing. Similar markets, moreover, exist for a number of other public figures, allowing users to gamble on whether 96-year-old actress Betty White and U.S. Senator John McCain — who has been diagnosed with brain cancer — will survive until Jan. 1, 2019.

This is why ethics in technology are important. There is no such thing as a ‘neutral’ technology:

Now that assassination markets are here, a fierce debate has emerged in cryptocurrency circles over what — if anything — should be done about them, as well as who should be held responsible for these clearly-illegal death markets.

The core issue stems from the fact that, in addition to the pure revulsion that these markets should engender in any decent human being, they also create a financial incentive for someone to place a large bet that a public figure will be assassinated and then murder that person for profit. Consequently, the mere presence of these markets makes it more likely that these events will occur, however slim that increase may be.

Interesting times, indeed.

Source: CCN

Ethical design in social networks

I’m thinking a lot about privacy and ethical design at the moment as part of my role leading Project MoodleNet. This article gives a short but useful overview of the Ethical Design Manifesto, along with some links for further reading:

There is often a disconnect between what digital designers originally intend with a product or feature, and how consumers use or interpret it.

Ethical user experience design – meaning, for example, designing technologies in ways that promote good online behaviour and intuit how they might be used – may help bridge that gap.

There’s already people (like me) making choices about the technology and social networks they used based on ethics:

User experience design and research has so far mainly been applied to designing tech that is responsive to user needs and locations. For example, commercial and digital assistants that intuit what you will buy at a local store based on your previous purchases.

However, digital designers and tech companies are beginning to recognise that there is an ethical dimension to their work, and that they have some social responsibility for the well-being of their users.

Meeting this responsibility requires designers to anticipate the meanings people might create around a particular technology.

In addition to ethical design, there are other elements to take into consideration:

Contextually aware design is capable of understanding the different meanings that a particular technology may have, and adapting in a way that is socially and ethically responsible. For example, smart cars that prevent mobile phone use while driving.

Emotional design refers to technology that elicits appropriate emotional responses to create positive user experiences. It takes into account the connections people form with the objects they use, from pleasure and trust to fear and anxiety.

This includes the look and feel of a product, how easy it is to use and how we feel after we have used it.

Anticipatory design allows technology to predict the most useful interaction within a sea of options and make a decision for the user, thus “simplifying” the experience. Some companies may use anticipatory design in unethical ways that trick users into selecting an option that benefits the company.

Source: The Conversation

Is it pointless to ban autonomous killing machines?

The authors do have a point:

Suppose the UN were to implement a preventive ban on the further development of all autonomous weapons technology. Further suppose – quite optimistically, already – that all armies around the world were to respect the ban, and abort their autonomous-weapons research programmes. Even with both of these assumptions in place, we would still have to worry about autonomous weapons. A self-driving car can be easily re-programmed into an autonomous weapons system: instead of instructing it to swerve when it sees a pedestrian, just teach it to run over the pedestrian.

Source: Aeon