Tag Archives: artificial intelligence

smart home gadgets

This article from MIT says this year’s CES (Consumer Electronics…what? anyway it’s the big annual consumer electronics expo in Las Vegas) was all about voice-controlled home gadgets. I’m excited about certain things. I like the idea of a video doorbell and smoke detectors that can text me if they sense something while I am not home, for example.

The main concern people seem to have is privacy. While that concerns me a little, I am more concerned about repair and replacement of all this stuff as it wears out. There are a lot of little things broken in my house right now. I know how to fix some of them. I know who to call on others, although it can be a royal pain to get them to actually show up, diagnose the problem, and then follow up until it fixed. My “home warranty”, which is really just a contract with a network of independent repair people, helps a little to get them to be responsive and follow up, but dealing with them is still a pain. While I am fixing things, other things are going to break. Things like keyholes and doorbells last at least 20 years with minor repairs, and traditional dumb appliances last 10 or so years with minor repairs. It is better to just accept that things break at a certain rate and deal with it than to get frustrated, although they do seem to have a tendency to break all at once when I have other challenges going on in my family and work life. I know there is absolutely nothing special about me and everyone deals with the same issues, except the super rich who can just pay someone else to worry about it.

Now, when we add all the smart technology to the dumb things in our home, they are still going to have most of the same dumb problems they have always had, requiring occasional minor repairs and replacement after 10-20 years. But the added technology is going to need some combination of physical repairs and tech support frequently, and it will probably need to be replaced every 2 or 3 years like any other electronic device. Except now it will be 100 little things breaking and needing replacement in your house. Probably, you will need some kind of service contract for someone to come check and fix things at least monthly.

AI and socialism

AI and algorithms are being used to target social services more precisely in Denmark. This article finds the level of data being collected on individuals insidious. I think it could be in the wrong hands, but this sort of thing seems to work in the Scandinavian countries where people actually trust their governments and neighbors. In the U.S., we tend to take paranoia to extremes, for example refusing to have a national ID card when it could solve some of our voter registration issues.

The municipality of Gladsaxe in Copenhagen, for example, has quietly been experimenting with a system that would use algorithms to identify children at risk of abuse, allowing authorities to target the flagged families for early intervention that could ultimately result in forced removals.

The children would be targeted based on specially designed algorithms tasked with crunching the information already gathered by the Danish government and linked to the personal identification number that is assigned to all Danes at birth. This information includes health records, employment information, and much more.

From the Danish government’s perspective, the child-welfare algorithm proposal is merely an extension of the systems it already has in place to detect social fraud and abuse. Benefits and entitlements covering millions of Danes have long been handled by a centralized agency (Udbetaling Danmark), and based on the vast amounts of personal data gathered and processed by this agency, algorithms create so-called puzzlement lists identifying suspicious patterns that may suggest fraud or abuse. These lists can then be acted on by the “control units” operated by many municipalities to investigate those suspected of receiving benefits to which they are not entitled. The data may include information on spouses and children, as well as information from financial institutions.

October 2018 in Review

Most frightening stories:

  • The Trump administration has slashed funding to help the U.S. prepare for the next pandemic.
  • I read more gloomy expert opinions on the stability and resilience of the global financial system.
  • A new depressing IPCC report came out. Basically, implementing the Paris agreement is too little, too late, and we are not even implementing it. There is at least some movement towards a carbon tax in the U.S. – a hopeful development, except that oil companies are in favor of it which makes it suspicious. There is a carbon tax initiative on the ballot in Washington State this November that the oil companies appear to be terrified of, so comparing the two could be instructive, and the industry strategy may be to get a weaker law at the federal level as protection against a patchwork of tough laws at the state and local levels.

Most hopeful stories:

  • There is no evidence that kids in U.S. private schools do any better than kids in U.S. public schools, once you control for family income. (Okay – I admit I put this in the hopeful column because I have kids in public school.)
  • Regenerative agriculture is an idea to sequester carbon by restoring soil and  protecting biodiversity on a global scale.
  • Applying nitrogen fixing bacteria to plants that do not naturally have them may be a viable way to reduce nitrogen fertilizer use and water pollution.

Most interesting stories, that were not particularly frightening or hopeful, or perhaps were a mixture of both:

  • New tech roundup: Artificial spider silk is an alternative to carbon fiber. Certain types of science, like drug and DNA experiments, can be largely automated. A “quantum internet” could mean essentially unbreakable encryption.
  • Modern monetary theory suggests governments might be able to print (okay, “create”) and spend a lot more money without serious repercussions. What I find odd about these discussions is they focus almost entirely on inflation and currency exchange values, while barely acknowledging that money has some relationship actual physical constraints. To me, it has always seemed that one function of the financial system is to start flashing warning lights and make us face the realities of how much we can do before we are all actually starving and freezing in the dark. It could be that we are in the midst of a long, slow slide in our ability to improve our physical quality of life, but instead of that manifesting itself as a long slow slide, it comes as a series of random shocks where one gets a little harder to recover from.
  • I read some interesting ideas on fair and unfair inequality. Conservative politicians encourage people not to make a distinction between alleviating poverty and the idea of making everybody equal. These are not the same thing at all because living just above the poverty line is no picnic and is not the same thing as being average. There is a strong moral case to be made that nobody “deserves” to live in poverty even if they have made some mistakes. And simply “creating jobs” in high-poverty areas sounds like a nice conservative alternative to handouts, except that there isn’t much evidence that it works.

applying the latest data science to intimate acts

WARNING: I never promised this would be a 100% family friendly blog. Nevertheless, it’s been awhile since I checked in on the latest sex robots. Well, this is a blog about the fabulous science fiction future, and we all need to face up to the fact that sex robots are likely to be a part of that.

Anyway, I offer this paper first of all because it’s funny, and second of all because even if it turns out to be a joke, the technology to analyze videos of thousands of hours of sexual acts, analyze them using the latest data science techniques, and program the results into a robot almost certainly all exist. Yesterday’s “phone sex” will almost certainly evolve into tomorrow’s virtual brothel. I think it is more or less harmless although it means the way real human beings interact with each other will continue to evolve. But that has been going on for a long time and there is no reason to think it should stop now.

 

MIT makes crazy AI on purpose

A group at MIT showed an AI algorithm really disturbing pictures and then asked it what it saw in some inkblots.

When a “normal” algorithm generated by artificial intelligence is asked what it sees in an abstract shape it chooses something cheery: “A group of birds sitting on top of a tree branch.”

Norman sees a man being electrocuted.

And where “normal” AI sees a couple of people standing next to each other, Norman sees a man jumping from a window.

The psychopathic algorithm was created by a team at the Massachusetts Institute of Technology, as part of an experiment to see what training AI on data from “the dark corners of the net” would do to its world view.

The software was shown images of people dying in gruesome circumstances, culled from a group on the website Reddit.

Then the AI, which can interpret pictures and describe what it sees in text form, was shown inkblot drawings and asked what it saw in them.

Personally, I’m afraid of the people who spend their time seeking out photos of people dying violently and posting them on Reddit. As for the algorithm, I suppose it could be trained to identify and block violent images like the ones it has been shown, or kiddie porn, or ads targeting minors, etc. Or in the wrong hands, it could be used to block political speech or repress certain people or groups. Or the highest bidding company could get to use it to repress competitors’ ads.

the French AI strategy

Other countries (than the United States) are developing strategies for how artificial intelligence will affect work, productivity, and growth in the near future.

France’s national strategy also reveals that Macron’s government is wrestling with how to ensure that AI supports inclusivity and diversity, and to make certain that its implementation is transparent. The French aren’t just theorizing; they’re taking action. France plans to invest 1.5 billion euros (almost $1.8 billion dollars) in the next five years in artificial intelligence research. The French are looking to create their own AI ecosystem, train the next generation of scientists and engineers, and make sure that their workforce is prepared for an automated future.

France isn’t alone. Last month, the European Union’s executive branch recommended its member states increase their public and private sector investment in AI. It also pledged billions in direct research spending. Meanwhile, China laid out its AI plan for global dominance last year, a plan that has also been backed up with massive investment. China’s goal is to lead the world in AI technology by 2030. Around the world, our global economic competitors are taking action on artificial intelligence.

It’s therefore striking that the United States doesn’t have a national artificial intelligence plan.

The fact that I don’t find it striking reflects my lowered expectations more than anything. We don’t really have a strategy for infrastructure or education either, for example.

quantum computers

There has been some progress on quantum computers.

Quantum computers, after decades of research, have nearly enough oomph to perform calculations beyond any other computer on Earth. Their killer app is usually said to be factoring large numbers, which are the key to modern encryption. That’s still another decade off, at least. But even today’s rudimentary quantum processors are uncannily matched to the needs of machine learning. They manipulate vast arrays of data in a single step, pick out subtle patterns that classical computers are blind to, and don’t choke on incomplete or uncertain data. “There is a natural combination between the intrinsic statistical nature of quantum computing … and machine learning,” said Johannes Otterbach, a physicist at Rigetti Computing, a quantum-computer company in Berkeley, California.

If anything, the pendulum has now swung to the other extreme. Google, Microsoft, IBM and other tech giants are pouring money into quantum machine learning, and a startup incubator at the University of Toronto is devoted to it. “‘Machine learning’ is becoming a buzzword,” said Jacob Biamonte, a quantum physicist at the Skolkovo Institute of Science and Technology in Moscow. “When you mix that with ‘quantum,’ it becomes a mega-buzzword.”

2017 in Review

Most frightening stories of 2017:

  • January: The U.S. government may be “planning to roll back or dilute many of the provisions of Dodd-Frank, particularly those that protect consumers from toxic financial products and those that impose restrictions on banks”.
  • February: The Doomsday Clock was moved to 2.5 minutes to midnight. The worst it has ever been was 2 minutes to midnight in the early 1980s. In related news, the idea of a U.S.-China war is looking a bit more plausible. The U.S. military may be considering sending ground troops to Syria.
  • March: La Paz, Bolivia, is in a serious crisis caused by loss of its glacier-fed water supply. At the same time we are losing glaciers and snowpack in important food-growing regions, the global groundwater situation is also looking bleak. And for those of us trying to do our little part for water conservation, investing in a residential graywater system can take around 15 years to break even at current costs and water rates.
  • April: The U.S. health care market is screwed up seemingly beyond repair. Why can’t we have nice things? Oh right, because our politicians represent big business, not voters. Also, we have forgotten the difference between a dialog and an argument.
  • May: We hit 410 ppm at Mauna Loa.
  • June: The Onion shared this uncharacteristically unfunny observation: “MYTH: There is nothing mankind can do to prevent climate change. FACT: There is nothing mankind will do to prevent climate change”. It’s not funny because it’s probably true.
  • July: Long term food security in Asia could be a problem.
  • August: The U.S. construction industry has had negligible productivity gains in the past 40 years.
  • September: During the Vietnam War the United States dropped approximately twice as many tons of bombs in Southeast Asia as the Allied forces combined used against both Germany and Japan in World War II. After the Cold War finally ended, Mikhail Gorbachev made some good suggestions for how to achieve a lasting peace. They were ignored. We may be witnessing the decline of the American Empire as a result.
  • October: It is possible that a catastrophic loss of insects is occurring and that it may lead to ecological collapse. Also, there is new evidence that pollution is harming human health and even the global economy more than previously thought.
  • November: I thought about war and peace in November. Well, mostly war. War is frightening. The United States of America appears to be flailing about militarily all over the world guided by no foreign policy. Big wars of the past have sometimes been started by overconfident leaders thinking they could get a quick military victory, only to find themselves bogged down in something much larger and more intractable than they imagined. But enemies are good to have – the Nazis understood that a scared population will believe what you tell them.
  • December: A lot of people would probably agree that the United States government is becoming increasingly dysfunctional, but I don’t think many would question the long-term stability of our form of government itself. Maybe we should start to do that. The Consumer Financial Protection Bureau has been doing a decent job of protecting consumers and reducing the risk of another financial crisis. The person in charge of it now was put there specifically to ruin it. Something similar may be about to happen at the Census Bureau. A U.S. Constitutional Convention is actually a possibility, and might threaten the stability of the nation.

Most hopeful stories of 2017:

Most interesting stories that weren’t particularly frightening or hopeful, or perhaps were a mixture of both:

  • January: Apple, Google, and Facebook may destroy the telecom industry.
  • February: The idea of growing human organs inside a pig, or even a viable human-pig hybrid, is getting very close. Tiny brains can also be grown on a microchip. Bringing back extinct animals is also getting very close.
  • March: Bill Gates has proposed a “robot tax”. The basic idea is that if and when automation starts to increase productivity, you could tax the increase in profits and use the money to help any workers displaced by the automation. In related somewhat boring economic news, there are a variety of theories as to why a raise in the minimum wage does not appear to cause unemployment as classical economic theory would predict.
  • April: I finished reading Rainbow’s End, a fantastic Vernor Vinge novel about augmented reality in the near future, among other things.
  • May: The sex robots are here.
  • June: “Fleur de lawn” is a mix of perennial rye, hard fescue, micro clover, yarrow, Achillea millefolium, sweet alyssum, Lobularia maritima, baby blue eyes, Nemophila menziesi, English daisy, Bellis perennis, and O’Connor’s strawberry clover, Trifolium fragiferum.
  • July: Ecologists have some new ideas for measuring resilience of ecosystems. Technologists have some wild ideas to have robots directly counteract the effects of humans on ecosystems. I like ideas – how do I get a (well-compensated) job where I can just sit around and think up ideas?
  • August: Elon Musk has thrown his energy into deep tunneling technology.
  • September: I learned that the OECD Science, Technology and Innovation Outlook named “ten key emerging technology trends”: The Internet of Things, Big data analytics, Artificial intelligence, Neurotechnologies, Nano/microsatellites, Nanomaterials, Additive manufacturing / 3D printing, Advanced energy storage technologies, Synthetic biology, Blockchain
  • October: Even if autonomous trucks are not ready for tricky urban situations, they could be autonomous on the highway with a small number of remote-control drivers guiding a large number of tricks through tricky urban maneuvers, not unlike the way ports or trainyards are run now. There is also new thinking on how to transition highways gradually through a mix of human and computer-controlled vehicles, and eventually to full computer control. New research shows that even a small number of autonomous vehicles mixed in with human drivers will be safer for everyone. While some reports predict autonomous taxis will be available in the 2020s, Google says that number is more like 2017.
  • November: It’s possible that the kind of ideal planned economy envisioned by early Soviet economists (which never came to pass) could be realized with the computing power and algorithms just beginning to be available now.
  • December: Microsoft is trying to one-up Google Scholar, which is good for researchers. More computing firepower is being focused on making sense of all the scientific papers out there.

I’ll keep this on the short side. Here are a few trends I see:

Risk of War. I think I said about a year ago that if we could through the next four years without a world war or nuclear detonation, we will be doing well. Well, one year down and three to go. That’s the bright side. The dark side is that it is time to acknowledge there is a regional war going on in the Middle East. It could escalate, it could go nuclear, and it could result in military confrontation between the United States and Russia. Likewise, the situation in North Korea could turn into a regional conflict, could go nuclear, and could lead to military confrontation between the United States and China.

Decline…and Fall? A question on my mind is whether the United States is a nation in decline, and I think the surprisingly obvious answer is yes. The more important question is whether it is a temporary dip, or the beginning of a decline and fall.

Risk of Financial Crisis. The risk of another serious financial crisis is even scarier that war in some ways, at least a limited, non-nuclear war. Surprisingly, the economic effects can be more severe, more widespread and longer lasting. We are seeing the continued weakening of regulations attempting to limit systemic risk-taking for short-term gain. Without a pickup in long-term productivity growth and with the demographic and ecological headwinds that we face, another crisis equal to or worse than the 2007 one could be the one that we don’t recover from.

Ecological Collapse? The story about vanishing insects was eye-opening to me. Could global ecosystems go into a freefall? Could populous regions of the world face a catastrophic food shortage? It is hard to imagine these things coming to a head in the near term, but the world needs to take these risks seriously since the consequences would be so great.

Technology. With everything else going on, technology just marches forward, of course. One technology I find particularly interesting is new approaches to research that mine and attempt to synthesize large bodies of scientific research.

Can the human species implement good ideas? Solutions exist. I would love to end on a positive note, but at the moment I find myself questioning whether our particular species of hairless ape can implement them.

But – how’s this for ending on a positive note – like I said at the beginning, the one thing about 2017 that definitely didn’t suck was that we didn’t get blown up!

Big-C and Little-C Consciousness

This article in KurzweilAI explains the competing “Big C” and “Little C” theories of consciousness.

Another viewpoint on consciousness comes from quantum theory, which is the deepest theory of physics. According to the orthodox Copenhagen Interpretation, consciousness and the physical world are complementary aspects of the same reality. When a person observes, or experiments on, some aspect of the physical world, that person’s conscious interaction causes discernible change. Since it takes consciousness as a given and no attempt is made to derive it from physics, the Copenhagen Interpretation may be called the “big-C” view of consciousness, where it is a thing that exists by itself – although it requires brains to become real. This view was popular with the pioneers of quantum theory such as Niels Bohr, Werner Heisenberg and Erwin Schrödinger.

The interaction between consciousness and matter leads to paradoxes that remain unresolved after 80 years of debate. A well-known example of this is the paradox of Schrödinger’s cat, in which a cat is placed in a situation that results in it being equally likely to survive or die – and the act of observation itself is what makes the outcome certain.

The opposing view is that consciousness emerges from biology, just as biology itself emerges from chemistry which, in turn, emerges from physics. We call this less expansive concept of consciousness “little-C.” It agrees with the neuroscientists’ view that the processes of the mind are identical to states and processes of the brain. It also agrees with a more recent interpretation of quantum theory motivated by an attempt to rid it of paradoxes, the Many Worlds Interpretation, in which observers are a part of the mathematics of physics.