Tag Archives: society

#432568 Tech Optimists See a Golden ...

Technology evangelists dream about a future where we’re all liberated from the more mundane aspects of our jobs by artificial intelligence. Other futurists go further, imagining AI will enable us to become superhuman, enhancing our intelligence, abandoning our mortal bodies, and uploading ourselves to the cloud.

Paradise is all very well, although your mileage may vary on whether these scenarios are realistic or desirable. The real question is, how do we get there?

Economist John Maynard Keynes notably argued in favor of active intervention when an economic crisis hits, rather than waiting for the markets to settle down to a more healthy equilibrium in the long run. His rebuttal to critics was, “In the long run, we are all dead.” After all, if it takes 50 years of upheaval and economic chaos for things to return to normality, there has been an immense amount of human suffering first.

Similar problems arise with the transition to a world where AI is intimately involved in our lives. In the long term, automation of labor might benefit the human species immensely. But in the short term, it has all kinds of potential pitfalls, especially in exacerbating inequality within societies where AI takes on a larger role. A new report from the Institute for Public Policy Research has deep concerns about the future of work.

Uneven Distribution
While the report doesn’t foresee the same gloom and doom of mass unemployment that other commentators have considered, the concern is that the gains in productivity and economic benefits from AI will be unevenly distributed. In the UK, jobs that account for £290 billion worth of wages in today’s economy could potentially be automated with current technology. But these are disproportionately jobs held by people who are already suffering from social inequality.

Low-wage jobs are five times more likely to be automated than high-wage jobs. A greater proportion of jobs held by women are likely to be automated. The solution that’s often suggested is that people should simply “retrain”; but if no funding or assistance is provided, this burden is too much to bear. You can’t expect people to seamlessly transition from driving taxis to writing self-driving car software without help. As we have already seen, inequality is exacerbated when jobs that don’t require advanced education (even if they require a great deal of technical skill) are the first to go.

No Room for Beginners
Optimists say algorithms won’t replace humans, but will instead liberate us from the dull parts of our jobs. Lawyers used to have to spend hours trawling through case law to find legal precedents; now AI can identify the most relevant documents for them. Doctors no longer need to look through endless scans and perform diagnostic tests; machines can do this, leaving the decision-making to humans. This boosts productivity and provides invaluable tools for workers.

But there are issues with this rosy picture. If humans need to do less work, the economic incentive is for the boss to reduce their hours. Some of these “dull, routine” parts of the job were traditionally how people getting into the field learned the ropes: paralegals used to look through case law, but AI may render them obsolete. Even in the field of journalism, there’s now software that will rewrite press releases for publication, traditionally something close to an entry-level task. If there are no entry-level jobs, or if entry-level now requires years of training, the result is to exacerbate inequality and reduce social mobility.

Automating Our Biases
The adoption of algorithms into employment has already had negative impacts on equality. Cathy O’Neil, mathematics PhD from Harvard, raises these concerns in her excellent book Weapons of Math Destruction. She notes that algorithms designed by humans often encode the biases of that society, whether they’re racial or based on gender and sexuality.

Google’s search engine advertises more executive-level jobs to users it thinks are male. AI programs predict that black offenders are more likely to re-offend than white offenders; they receive correspondingly longer sentences. It needn’t necessarily be that bias has been actively programmed; perhaps the algorithms just learn from historical data, but this means they will perpetuate historical inequalities.

Take candidate-screening software HireVue, used by many major corporations to assess new employees. It analyzes “verbal and non-verbal cues” of candidates, comparing them to employees that historically did well. Either way, according to Cathy O’Neil, they are “using people’s fear and trust of mathematics to prevent them from asking questions.” With no transparency or understanding of how the algorithm generates its results, and no consensus over who’s responsible for the results, discrimination can occur automatically, on a massive scale.

Combine this with other demographic trends. In rich countries, people are living longer. An increasing burden will be placed on a shrinking tax base to support that elderly population. A recent study said that due to the accumulation of wealth in older generations, millennials stand to inherit more than any previous generation, but it won’t happen until they’re in their 60s. Meanwhile, those with savings and capital will benefit as the economy shifts: the stock market and GDP will grow, but wages and equality will fall, a situation that favors people who are already wealthy.

Even in the most dramatic AI scenarios, inequality is exacerbated. If someone develops a general intelligence that’s near-human or super-human, and they manage to control and monopolize it, they instantly become immensely wealthy and powerful. If the glorious technological future that Silicon Valley enthusiasts dream about is only going to serve to make the growing gaps wider and strengthen existing unfair power structures, is it something worth striving for?

What Makes a Utopia?
We urgently need to redefine our notion of progress. Philosophers worry about an AI that is misaligned—the things it seeks to maximize are not the things we want maximized. At the same time, we measure the development of our countries by GDP, not the quality of life of workers or the equality of opportunity in the society. Growing wealth with increased inequality is not progress.

Some people will take the position that there are always winners and losers in society, and that any attempt to redress the inequalities of our society will stifle economic growth and leave everyone worse off. Some will see this as an argument for a new economic model, based around universal basic income. Any moves towards this will need to take care that it’s affordable, sustainable, and doesn’t lead towards an entrenched two-tier society.

Walter Schiedel’s book The Great Leveller is a huge survey of inequality across all of human history, from the 21st century to prehistoric cave-dwellers. He argues that only revolutions, wars, and other catastrophes have historically reduced inequality: a perfect example is the Black Death in Europe, which (by reducing the population and therefore the labor supply that was available) increased wages and reduced inequality. Meanwhile, our solution to the financial crisis of 2007-8 may have only made the problem worse.

But in a world of nuclear weapons, of biowarfare, of cyberwarfare—a world of unprecedented, complex, distributed threats—the consequences of these “safety valves” could be worse than ever before. Inequality increases the risk of global catastrophe, and global catastrophes could scupper any progress towards the techno-utopia that the utopians dream of. And a society with entrenched inequality is no utopia at all.

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#432512 How Will Merging Minds and Machines ...

One of the most exciting and frightening outcomes of technological advancement is the potential to merge our minds with machines. If achieved, this would profoundly boost our cognitive capabilities. More importantly, however, it could be a revolution in human identity, emotion, spirituality, and self-awareness.

Brain-machine interface technology is already being developed by pioneers and researchers around the globe. It’s still early and today’s tech is fairly rudimentary, but it’s a fast-moving field, and some believe it will advance faster than generally expected. Futurist Ray Kurzweil has predicted that by the 2030s we will be able to connect our brains to the internet via nanobots that will “provide full-immersion virtual reality from within the nervous system, provide direct brain-to-brain communication over the internet, and otherwise greatly expand human intelligence.” Even if the advances are less dramatic, however, they’ll have significant implications.

How might this technology affect human consciousness? What about its implications on our sentience, self-awareness, or subjective experience of our illusion of self?

Consciousness can be hard to define, but a holistic definition often encompasses many of our most fundamental capacities, such as wakefulness, self-awareness, meta-cognition, and sense of agency. Beyond that, consciousness represents a spectrum of awareness, as seen across various species of animals. Even humans experience different levels of existential awareness.

From psychedelics to meditation, there are many tools we already use to alter and heighten our conscious experience, both temporarily and permanently. These tools have been said to contribute to a richer life, with the potential to bring experiences of beauty, love, inner peace, and transcendence. Relatively non-invasive, these tools show us what a seemingly minor imbalance of neurochemistry and conscious internal effort can do to the subjective experience of being human.

Taking this into account, what implications might emerging brain-machine interface technologies have on the “self”?

The Tools for Self-Transcendence
At the basic level, we are currently seeing the rise of “consciousness hackers” using techniques like non-invasive brain stimulation through EEG, nutrition, virtual reality, and ecstatic experiences to create environments for heightened consciousness and self-awareness. In Stealing Fire, Steven Kotler and Jamie Wheal explore this trillion-dollar altered-states economy and how innovators and thought leaders are “harnessing rare and controversial states of consciousness to solve critical challenges and outperform the competition.” Beyond enhanced productivity, these altered states expose our inner potential and give us a glimpse of a greater state of being.

Expanding consciousness through brain augmentation and implants could one day be just as accessible. Researchers are working on an array of neurotechnologies as simple and non-invasive as electrode-based EEGs to invasive implants and techniques like optogenetics, where neurons are genetically reprogrammed to respond to pulses of light. We’ve already connected two brains via the internet, allowing the two to communicate, and future-focused startups are researching the possibilities too. With an eye toward advanced brain-machine interfaces, last year Elon Musk unveiled Neuralink, a company whose ultimate goal is to merge the human mind with AI through a “neural lace.”

Many technologists predict we will one day merge with and, more speculatively, upload our minds onto machines. Neuroscientist Kenneth Hayworth writes in Skeptic magazine, “All of today’s neuroscience models are fundamentally computational by nature, supporting the theoretical possibility of mind-uploading.” This might include connecting with other minds using digital networks or even uploading minds onto quantum computers, which can be in multiple states of computation at a given time.

In their book Evolving Ourselves, Juan Enriquez and Steve Gullans describe a world where evolution is no longer driven by natural processes. Instead, it is driven by human choices, through what they call unnatural selection and non-random mutation. With advancements in genetic engineering, we are indeed seeing evolution become an increasingly conscious process with an accelerated pace. This could one day apply to the evolution of our consciousness as well; we would be using our consciousness to expand our consciousness.

What Will It Feel Like?
We may be able to come up with predictions of the impact of these technologies on society, but we can only wonder what they will feel like subjectively.

It’s hard to imagine, for example, what our stream of consciousness will feel like when we can process thoughts and feelings 1,000 times faster, or how artificially intelligent brain implants will impact our capacity to love and hate. What will the illusion of “I” feel like when our consciousness is directly plugged into the internet? Overall, what impact will the process of merging with technology have on the subjective experience of being human?

The Evolution of Consciousness
In The Future Evolution of Consciousness, Thomas Lombardo points out, “We are a journey rather than a destination—a chapter in the evolutionary saga rather than a culmination. Just as probable, there will also be a diversification of species and types of conscious minds. It is also very likely that new psychological capacities, incomprehensible to us, will emerge as well.”

Humans are notorious for fearing the unknown. For any individual who has never experienced an altered state, be it spiritual or psychedelic-induced, it is difficult to comprehend the subjective experience of that state. It is why many refer to their first altered-state experience as “waking up,” wherein they didn’t even realize they were asleep.

Similarly, exponential neurotechnology represents the potential of a higher state of consciousness and a range of experiences that are unimaginable to our current default state.

Our capacity to think and feel is set by the boundaries of our biological brains. To transform and expand these boundaries is to transform and expand the first-hand experience of consciousness. Emerging neurotechnology may end up providing the awakening our species needs.

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#432303 What If the AI Revolution Is Neither ...

Why does everyone assume that the AI revolution will either lead to a fiery apocalypse or a glorious utopia, and not something in between? Of course, part of this is down to the fact that you get more attention by saying “The end is nigh!” or “Utopia is coming!”

But part of it is down to how humans think about change, especially unprecedented change. Millenarianism doesn’t have anything to do with being a “millennial,” being born in the 90s and remembering Buffy the Vampire Slayer. It is a way of thinking about the future that involves a deeply ingrained sense of destiny. A definition might be: “Millenarianism is the expectation that the world as it is will be destroyed and replaced with a perfect world, that a redeemer will come to cast down the evil and raise up the righteous.”

Millenarian beliefs, then, intimately link together the ideas of destruction and creation. They involve the idea of a huge, apocalyptic, seismic shift that will destroy the fabric of the old world and create something entirely new. Similar belief systems exist in many of the world’s major religions, and also the unspoken religion of some atheists and agnostics, which is a belief in technology.

Look at some futurist beliefs around the technological Singularity. In Ray Kurzweil’s vision, the Singularity is the establishment of paradise. Everyone is rendered immortal by biotechnology that can cure our ills; our brains can be uploaded to the cloud; inequality and suffering wash away under the wave of these technologies. The “destruction of the world” is replaced by a Silicon Valley buzzword favorite: disruption. And, as with many millenarian beliefs, your mileage varies on whether this destruction paves the way for a new utopia—or simply ends the world.

There are good reasons to be skeptical and interrogative towards this way of thinking. The most compelling reason is probably that millenarian beliefs seem to be a default mode of how humans think about change; just look at how many variants of this belief have cropped up all over the world.

These beliefs are present in aspects of Christian theology, although they only really became mainstream in their modern form in the 19th and 20th centuries. Ideas like the Tribulations—many years of hardship and suffering—before the Rapture, when the righteous will be raised up and the evil punished. After this destruction, the world will be made anew, or humans will ascend to paradise.

Despite being dogmatically atheist, Marxism has many of the same beliefs. It is all about a deterministic view of history that builds to a crescendo. In the same way as Rapture-believers look for signs that prophecies are beginning to be fulfilled, so Marxists look for evidence that we’re in the late stages of capitalism. They believe that, inevitably, society will degrade and degenerate to a breaking point—just as some millenarian Christians do.

In Marxism, this is when the exploitation of the working class by the rich becomes unsustainable, and the working class bands together and overthrows the oppressors. The “tribulation” is replaced by a “revolution.” Sometimes revolutionary figures, like Lenin, or Marx himself, are heralded as messiahs who accelerate the onset of the Millennium; and their rhetoric involves utterly smashing the old system such that a new world can be built. Of course, there is judgment, when the righteous workers take what’s theirs and the evil bourgeoisie are destroyed.

Even Norse mythology has an element of this, as James Hughes points out in his essay in Nick Bostrom’s book Global Catastrophic Risks. Ragnarok involves men and gods being defeated in a final, apocalyptic battle—but because that was a little bleak, they add in the idea that a new earth will arise where the survivors will live in harmony.

Judgement day is a cultural trope, too. Take the ancient Egyptians and their beliefs around the afterlife; the Lord of the underworld, Osiris, weighs the mortal’s heart against a feather. “Should the heart of the deceased prove to be heavy with wrongdoing, it would be eaten by a demon, and the hope of an afterlife vanished.”

Perhaps in the Singularity, something similar goes on. As our technology and hence our power improve, a final reckoning approaches: our hearts, as humans, will be weighed against a feather. If they prove too heavy with wrongdoing—with misguided stupidity, with arrogance and hubris, with evil—then we will fail the test, and we will destroy ourselves. But if we pass, and emerge from the Singularity and all of its threats and promises unscathed, then we will have paradise. And, like the other belief systems, there’s no room for non-believers; all of society is going to be radically altered, whether you want it to be or not, whether it benefits you or leaves you behind. A technological rapture.

It almost seems like every major development provokes this response. Nuclear weapons did, too. Either this would prove the final straw and we’d destroy ourselves, or the nuclear energy could be harnessed to build a better world. People talked at the dawn of the nuclear age about electricity that was “too cheap to meter.” The scientists who worked on the bomb often thought that with such destructive power in human hands, we’d be forced to cooperate and work together as a species.

When we see the same response over and over again to different circumstances, cropping up in different areas, whether it’s science, religion, or politics, we need to consider human biases. We like millenarian beliefs; and so when the idea of artificial intelligence outstripping human intelligence emerges, these beliefs spring up around it.

We don’t love facts. We don’t love information. We aren’t as rational as we’d like to think. We are creatures of narrative. Physicists observe the world and we weave our observations into narrative theories, stories about little billiard balls whizzing around and hitting each other, or space and time that bend and curve and expand. Historians try to make sense of an endless stream of events. We rely on stories: stories that make sense of the past, justify the present, and prepare us for the future.

And as stories go, the millenarian narrative is a brilliant and compelling one. It can lead you towards social change, as in the case of the Communists, or the Buddhist uprisings in China. It can justify your present-day suffering, if you’re in the tribulation. It gives you hope that your life is important and has meaning. It gives you a sense that things are evolving in a specific direction, according to rules—not just randomly sprawling outwards in a chaotic way. It promises that the righteous will be saved and the wrongdoers will be punished, even if there is suffering along the way. And, ultimately, a lot of the time, the millenarian narrative promises paradise.

We need to be wary of the millenarian narrative when we’re considering technological developments and the Singularity and existential risks in general. Maybe this time is different, but we’ve cried wolf many times before. There is a more likely, less appealing story. Something along the lines of: there are many possibilities, none of them are inevitable, and lots of the outcomes are less extreme than you might think—or they might take far longer than you think to arrive. On the surface, it’s not satisfying. It’s so much easier to think of things as either signaling the end of the world or the dawn of a utopia—or possibly both at once. It’s a narrative we can get behind, a good story, and maybe, a nice dream.

But dig a little below the surface, and you’ll find that the millenarian beliefs aren’t always the most promising ones, because they remove human agency from the equation. If you think that, say, the malicious use of algorithms, or the control of superintelligent AI, are serious and urgent problems that are worth solving, you can’t be wedded to a belief system that insists utopia or dystopia are inevitable. You have to believe in the shades of grey—and in your own ability to influence where we might end up. As we move into an uncertain technological future, we need to be aware of the power—and the limitations—of dreams.

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#432279 This Week’s Awesome Stories From ...

Google Thinks It’s Close to ‘Quantum Supremacy.’ Here’s What That Really Means.
Martin Giles and Will Knight | MIT Technology Review
“Seventy-two may not be a large number, but in quantum computing terms, it’s massive. This week Google unveiled Bristlecone, a new quantum computing chip with 72 quantum bits, or qubits—the fundamental units of computation in a quantum machine…John Martinis, who heads Google’s effort, says his team still needs to do more testing, but he thinks it’s ‘pretty likely’ that this year, perhaps even in just a few months, the new chip can achieve ‘quantum supremacy.'”

How Project Loon Built the Navigation System That Kept Its Balloons Over Puerto Rico
Amy Nordrum | IEEE Spectrum
“Last year, Alphabet’s Project Loon made a big shift in the way it flies its high-altitude balloons. And that shift—from steering every balloon in a huge circle around the world to clustering balloons over specific areas—allowed the project to provide basic Internet service to more than 200,000 people in Puerto Rico after Hurricane Maria.”

The Grim Conclusions of the Largest-Ever Study of Fake News
Robinson Meyer | The Atlantic
“The massive new study analyzes every major contested news story in English across the span of Twitter’s existence—some 126,000 stories, tweeted by 3 million users, over more than 10 years—and finds that the truth simply cannot compete with hoax and rumor.”

Magic Leap Raises $461 Million in Fresh Funding From the Kingdom of Saudi Arabia
Lucas Matney | TechCrunch
“Magic Leap still hasn’t released a product, but they’re continuing to raise a lot of cash to get there. The Plantation, Florida-based augmented reality startup announced today that it has raised $461 million from the Kingdom of Saudi Arabia’s sovereign investment arm, The Public Investment Fund…Magic Leap has raised more than $2.3 billion in funding to date.”

Social Inequality Will Not Be Solved by an App
Safiya Umoja Noble | Wired
“An app will not save us. We will not sort out social inequality lying in bed staring at smartphones. It will not stem from simply sending emails to people in power, one person at a time…We need more intense attention on how these types of artificial intelligence, under the auspices of individual freedom to make choices, forestall the ability to see what kinds of choices we are making and the collective impact of these choices in reversing decades of struggle for social, political, and economic equality. Digital technologies are implicated in these struggles.”

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#432249 New Malicious AI Report Outlines Biggest ...

Everyone’s talking about deep fakes: audio-visual imitations of people, generated by increasingly powerful neural networks, that will soon be indistinguishable from the real thing. Politicians are regularly laid low by scandals that arise from audio-visual recordings. Try watching the footage that could be created of Barack Obama from his speeches, and the Lyrebird impersonations. You could easily, today or in the very near future, create a forgery that might be indistinguishable from the real thing. What would that do to politics?

Once the internet is flooded with plausible-seeming tapes and recordings of this sort, how are we going to decide what’s real and what isn’t? Democracy, and our ability to counteract threats, is already threatened by a lack of agreement on the facts. Once you can’t believe the evidence of your senses anymore, we’re in serious trouble. Ultimately, you can dream up all kinds of utterly terrifying possibilities for these deep fakes, from fake news to blackmail.

How to solve the problem? Some have suggested that media websites like Facebook or Twitter should carry software that probes every video to see if it’s a deep fake or not and labels the fakes. But this will prove computationally intensive. Plus, imagine a case where we have such a system, and a fake is “verified as real” by news media algorithms that have been fooled by clever hackers.

The other alternative is even more dystopian: you can prove something isn’t true simply by always having an alibi. Lawfare describes a “solution” where those concerned about deep fakes have all of their movements and interactions recorded. So to avoid being blackmailed or having your reputation ruined, you just consent to some company engaging in 24/7 surveillance of everything you say or do and having total power over that information. What could possibly go wrong?

The point is, in the same way that you don’t need human-level, general AI or humanoid robotics to create systems that can cause disruption in the world of work, you also don’t need a general intelligence to threaten security and wreak havoc on society. Andrew Ng, AI researcher, says that worrying about the risks from superintelligent AI is like “worrying about overpopulation on Mars.” There are clearly risks that arise even from the simple algorithms we have today.

The looming issue of deep fakes is just one of the threats considered by the new malicious AI report, which has co-authors from the Future of Humanity Institute and the Centre for the Study of Existential Risk (among other organizations.) They limit their focus to the technologies of the next five years.

Some of the concerns the report explores are enhancements to familiar threats.

Automated hacking can get better, smarter, and algorithms can adapt to changing security protocols. “Phishing emails,” where people are scammed by impersonating someone they trust or an official organization, could be generated en masse and made more realistic by scraping data from social media. Standard phishing works by sending such a great volume of emails that even a very low success rate can be profitable. Spear phishing aims at specific targets by impersonating family members, but can be labor intensive. If AI algorithms enable every phishing scam to become sharper in this way, more people are going to get gouged.

Then there are novel threats that come from our own increasing use of and dependence on artificial intelligence to make decisions.

These algorithms may be smart in some ways, but as any human knows, computers are utterly lacking in common sense; they can be fooled. A rather scary application is adversarial examples. Machine learning algorithms are often used for image recognition. But it’s possible, if you know a little about how the algorithm is structured, to construct the perfect level of noise to add to an image, and fool the machine. Two images can be almost completely indistinguishable to the human eye. But by adding some cleverly-calculated noise, the hackers can fool the algorithm into thinking an image of a panda is really an image of a gibbon (in the OpenAI example). Research conducted by OpenAI demonstrates that you can fool algorithms even by printing out examples on stickers.

Now imagine that instead of tricking a computer into thinking that a panda is actually a gibbon, you fool it into thinking that a stop sign isn’t there, or that the back of someone’s car is really a nice open stretch of road. In the adversarial example case, the images are almost indistinguishable to humans. By the time anyone notices the road sign has been “hacked,” it could already be too late.

As the OpenAI foundation freely admits, worrying about whether we’d be able to tame a superintelligent AI is a hard problem. It looks all the more difficult when you realize some of our best algorithms can be fooled by stickers; even “modern simple algorithms can behave in ways we do not intend.”

There are ways around this approach.

Adversarial training can generate lots of adversarial examples and explicitly train the algorithm not to be fooled by them—but it’s costly in terms of time and computation, and puts you in an arms race with hackers. Many strategies for defending against adversarial examples haven’t proved adaptive enough; correcting against vulnerabilities one at a time is too slow. Moreover, it demonstrates a point that can be lost in the AI hype: algorithms can be fooled in ways we didn’t anticipate. If we don’t learn about these vulnerabilities until the algorithms are everywhere, serious disruption can occur. And no matter how careful you are, some vulnerabilities are likely to remain to be exploited, even if it takes years to find them.

Just look at the Meltdown and Spectre vulnerabilities, which weren’t widely known about for more than 20 years but could enable hackers to steal personal information. Ultimately, the more blind faith we put into algorithms and computers—without understanding the opaque inner mechanics of how they work—the more vulnerable we will be to these forms of attack. And, as China dreams of using AI to predict crimes and enhance the police force, the potential for unjust arrests can only increase.

This is before you get into the truly nightmarish territory of “killer robots”—not the Terminator, but instead autonomous or consumer drones which could potentially be weaponized by bad actors and used to conduct attacks remotely. Some reports have indicated that terrorist organizations are already trying to do this.

As with any form of technology, new powers for humanity come with new risks. And, as with any form of technology, closing Pandora’s box will prove very difficult.

Somewhere between the excessively hyped prospects of AI that will do everything for us and AI that will destroy the world lies reality: a complex, ever-changing set of risks and rewards. The writers of the malicious AI report note that one of their key motivations is ensuring that the benefits of new technology can be delivered to people as quickly, but as safely, as possible. In the rush to exploit the potential for algorithms and create 21st-century infrastructure, we must ensure we’re not building in new dangers.

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