Month: July 2023

To What End?

~ Taran ~ 1 Comment

Sometimes it’s worth wondering about whether something is worth the hassle. An example this week was over a parking incident. I am, at present, stuck parking between 2 larger vehicles who are hemmed in by posts on either side.

For a while, one of the owners of the spot wasn’t using theirs, so I gave the other guy much more space so that he and his wife could get in and out of the vehicle. The owner of the other spot had a stroke and wasn’t able to drive, and recently someone started using his spot – I believe his son – and with their large vehicle, with poorly painted lines, it can be a challenge to park. I completely get that.

As it happens, the newer person parked closer to my spot, and so to make space for him to get in and out of his vehicle, I ate the line a bit on the other side. We’ve all dealt with this at some point, parking isn’t something that is necessarily as exact as we would like it to be and sometimes things happen.

I didn’t think much of it.

I got a message the next day from the other guy’s wife about her having to get out of the vehicle before her husband parked, which for one incident seemed… petty. So I explained to her on WhatsApp why these things happen, which I should not have to do for anyone who has been alive for more than 2 decades these days. Her husband has been alive 6, her, maybe 4 or 5. This should not have been a thing given I’ve been parking next to them without incident for about 4 years.

Knowing the sort of people they were I stopped by the property manager’s office and started off with, “You know, in case this guy comes and talks to you…”

My instincts were right. He had been there already. No surprise, I explained it to the property manager and I explained that I will always make sure that other drivers will be able to get in and out of their vehicle – but passengers, with the size of the vehicles we’re dealing with as well as the size of the spots, may not be able to.

I got a new message from the wife, saying that they were working out ways for me to get in and out of my vehicle – which was never an issue. If I have a problem, I work it out. I haven’t run into the person using the other spot yet, but I do believe he’s trying to get used to parking in that spot and he and I have only had once issue which the married couple just won’t let go. Because she had to get out of the car before her husband parked.

Once.

At this point, I had spent an hour on the issue with messages. It seemed ridiculous to me, but the world seems ridiculous to me so when I saw my psychologist I brought it up. So we used 10 minutes of her time, and mine, talking about it, and she assured me I wasn’t being crazy about it. Now we’re looking at my time, which is now at 1 hour and 10 minutes, and her time, 10 minutes, the property manager and the administrator who I spent 5 minutes with and who the husband probably spent 10-15 minutes with… and we’re looking at an hour and 40 minutes of ‘people time’.

Over one incident. Over a mild inconvenience.

And at the end of it – I hope this is the end of it – the husband sends a message that he’ll try to park closer to the post in the future, ‘alcohol permitting’.

I wonder sometimes whether people really consider how much time they waste on stupid stuff… and how much time they make others waste on stupid stuff.

10 years ago, I would have just told them what I thought about the whole thing from the start and let it go, leaving them to sort things out on their own.

I think it’s time to go back to doing that.

This is how productive time is lost. And productive time, either for business or for personal reasons, should trump stupid every time – and we need to make it so that it is.

Take back your time.

The Trouble With Predictions.

~ Taran ~ 1 Comment

We like predictions, particularly if we like the outcomes. We all want the winning lottery ticket because we want that outcome for a small investment. As individuals, we like to beat the odds. Collectively it breaks up into groups who want certain outcomes, and wars have been fought and continue to be fought over certain outcomes.

In fact, in conversation with a friend over coffee a few days ago I mentioned that in watching a documentary series on chimpanzees, their social groups have territory that they patrol and fight over, which include the richest fruit trees. In this regard we are not too different, we simply fight over other things. If we fought over trees, our world would likely be much different, more lush, with what we would consider less progress.

When I summarized the technological singularity, I didn’t really mention the other predictive models out there about other things because the technological singularity was a focal point. That’s the trouble with predictions. They have a tendency to omit other data. Let’s go with the 2045 technological singularity prediction, based predominantly on technology. What other factors will impact humanity by 2045?

There’s population, which I was surprised to find has decreased in growth rate. By 2045, though, we should have a global population of about 9 billion people – but here’s where it gets interesting.

Many factors contribute to the waxing and waning of the world’s population, such as migration, mortality, longevity and other major demographic metrics. Focusing on fertility, however, helps to illuminate why the total number of humans on Earth seems set to fall. Demographers define fertility as the average total number of live births per female individual in a region or country. (In the accompanying graphics, the term “woman” is used to encompass anyone assigned female at birth.) The U.S.’s present fertility rate, for example, is about 1.7; China’s is 1.2. Demographers consider a fertility rate of 2.1 to be the replacement rate—that is, the required number of offspring, on average, for a population to hold steady. Today birth rates in the wealthiest countries are below the replacement rate. About 50 percent of all nations fall below the replacement rate, and in 2022 the region with the lowest fertility rate (0.8) was Hong Kong.

Katie Peek, “Global Population Growth Is Slowing Down. Here’s One Reason Why“, Scientific American, December 7, 2022, (emphasis mine)

For simplification, we look at only the fertility metrics. Migration prediction is a mess because of laws and lines drawn on maps long ago. The data, however, demonstrates a decline and yet in the same article we see something interesting along those lines, which points to a need for migration.

High-income nations now have the lowest birth rates, and the lowest-income nations currently have the highest birth rates. “The gap has continued to widen between wealthy nations and poorer ones,” says Jennifer Sciubba, a social scientist at the Wilson Center in Washington, D.C., who has written about these planetary-scale demographic shifts. “But longer term,” she says, “we’re moving toward convergence.” In other words, this disparity among nations’ birth rates isn’t a permanent chasm. It’s a temporary divide that will narrow over the coming decades.

Katie Peek, “Global Population Growth Is Slowing Down. Here’s One Reason Why“, Scientific American, December 7, 2022, (emphasis mine)

How could we move toward that convergence without migration, particularly with economic disparity increasing even as we claim global poverty is diminishing? The global economics of nations has a role to play here as well. It’s not hard to see how the global population by itself might be around 9 billion in 2045, but where will those people live, and how will they live?

Let’s factor in something else, such as sea water levels. We attribute much of it to climate change. Pumping water out of aquifers faster than they can replenish is also a factor. I also stumbled across a few articles about how trees seemingly bend the laws of physics in storing water, and since a tree is roughly 50% water by mass, every time we cut down a tree half of it’s mass is released into the atmosphere as water.

It is interesting to note that as we cut down trees, we not only affect the ratio of gases in the air, a living thing by itself, but also release that moisture into the atmosphere where it will likely end up in the ocean that will contribute to sea level rise. How much is that? I don’t know, but since we have been doing it for generations I expect that it has been a significant amount.

Where do we find water to irrigate new tree growth when we plant them? Rains, the local aquifer, etc. Planting trees may well pull moisture out of the air, but does it do so at a rate greater than we pump water out of the ground to irrigate them?

And how much water do we store in our bodies? Roughly 60% of our body is water, and assuming a 75kg (approximately 165 pounds) person, each person would have about 45 liters (12 gallons) per human. We also store water. When we get buried, it goes into the local aquifer, when we get cremated, it goes into the atmosphere.

To maintain that level of water in our systems, which we conveniently find all over in plastic bottles these days, we need 3.7 litres (men) or 2.7 litres (women) per day. With a population of over 8 billion at this time, that’s a lot of water, and desalinization seems a great idea for assuring a better replenishment of the aquifers we’re pumping water out of. Yet we are bound by our own economics in this regard, about how cost-effective it is to do these things, particularly in less economically advantaged nations.

Oh, and we’re looking at increasing to 9 billion humans around 2045, but that number is based on fertility alone. There are a lot of other factors, which include water – which is also another factor.

Toss in politics and geography of materials for technology, it’s hard to look at a prediction like that of the technological singularity and be a bit boggled by the hubris. Now, if we could get all this data from all these silos to interact in ways that are cross-disciplinary, which an artificial intelligence could be good at, we might get less imperfect predictions.

That might be a great use of AI.

The Nature of How We Perceive AI.

~ Taran ~ Leave a comment

I began my more formal artificial intelligence reading begun around 1989 with Roger Penrose’s “The Emperor’s New Mind: Concerning Computers, Minds, and the Laws of Physics“, a gift from my father for some birthday or the other. I dreamed of a day where I could work with such systems and I spent much of my spare time over the years pondering it, and even experimenting with neural networks.

Of course, I never got to the point where we are now, where large corporations throw teams of people at it with a budget of a small nation’s GDP. I was too busy making a living as a software engineer and very rarely did I get to apply the arcane knowledge to work.

Stepping back from the incessant jabbering about artificial intelligence in the media, which has become increasingly redundant with nothing very new being added, I’m going to map how I viewed artificial intelligence over the ears.

The initial dream was to have something that could help solve problems of global importance. This is the dream of a teenager, someone who had not yet really been left unsupervised in the world, but someone who was also fiercely independent and individual. Like most teenagers, I wanted to bend the world to what I wanted, and with the PC revolution in full swing and the monthly periodicals showing up at the local bookstore making everything look possible, the sky seemed the limit.

The dream continued, as dreams do, and science fiction played a large role in that as well. Something peculiar happened along the way. I started understanding people better, and looking back on that period it was because much of how we look at artificial intelligence comes from who we are. We define it as a solution to the problems we define, much like any other technology.

The trouble is most of the time these days, it’s what we created that is the problem. This isn’t some tree-hugging hippy rhetoric, it’s a statement of fact. We created feast at the cost of famine, we created focal global markets at the cost of local diversity, and most of what we consider important as humans has little to do with anything outside our little isolated bubble of humanity in the cosmos. I don’t know what aliens would make of “Miss Universe”. Do you? There’s a writing prompt.

So when we look at artificial intelligence, we’re looking at it as a tool to solve our problems. This is important to understand, because we have not yet all agreed on the problems, and while messiah’s of technological singularity are having their 15 minutes of fame, we still haven’t gotten down to what we actually want collectively because…

We never agreed in the first place. That would be a starting point. Defining the use of artificial intelligence. Ask 20 people for better than vague answers, you’ll likely get 20+ definitions.

Wikipedia, AI, Oh My.

~ Taran ~ 2 Comments

One of the most disruptive things that has happened during Web 2.0 is Wikipedia – displacing the Encyclopedia Britannica as an online resource, forging strategic partnerships, and – for better and worse – the editorial community.

It has become one of the more dependable sources of information on the Internet, and while imperfect, the editors have collectively been a part of an evolution of verification and quality control that has made Wikipedia a staple.

It apparently has also been part of the training models of the large language models that we have grown to know over the past months, such as ChatGPT and Google’s Bard, which is interesting given how much volunteer work went into creating Wikipedia – something that makes me wonder if Wikimedia could be a part of the lawsuit.

This is pure speculation on my part, but given how much collective effort has gone into the many projects of Wikimedia, and given it’s mission is pretty clear about bringing free educational content to the world, large language models charging subscribers on that content is something that might be worth a bit of thought.

On a conference call in March that focused on A.I.’s threats to Wikipedia, as well as the potential benefits, the editors’ hopes contended with anxiety. While some participants seemed confident that generative A.I. tools would soon help expand Wikipedia’s articles and global reach, others worried about whether users would increasingly choose ChatGPT — fast, fluent, seemingly oracular — over a wonky entry from Wikipedia. A main concern among the editors was how Wikipedians could defend themselves from such a threatening technological interloper. And some worried about whether the digital realm had reached a point where their own organization — especially in its striving for accuracy and truthfulness — was being threatened by a type of intelligence that was both factually unreliable and hard to contain.

One conclusion from the conference call was clear enough: We want a world in which knowledge is created by humans. But is it already too late for that?

John Gertner, “Wikipedia’s Moment of Truth“, New York Times Magazine, July 18th, 2023, Updated on July 19th, 2023.

It is a quandary, that’s for sure. Speaking for myself, I prefer having citations on a Wikipedia page that I can research on my own – there seem to be at least some of us that trample our way through footnotes – and large language models don’t cite anything, which is the main problem I have with them.

In the facts category, I would say Wikipedia should win.

Unfortunately, time and again, the world has demonstrated that facts are sometimes a liability for selling a story, and so the concern I have is real.

Yet it could be useful to combine the two somehow.

Troubleshooting the Error: A Real World Example.

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Yesterday, tapping away at my keyboard on my laptop, my screen flickered black. I sighed. “Maybe it was a one off with some background process”, I thought, going about my business. It was 3:22 pm.

It flickered again. I started paying attention. It did it again.

Now I paid attention to the screen because when I write, I generally don’t look at the screen. I’ve been typing that long where I can look outside at the trees blowing in the wind and only glance at the screen as I need to. As I just did with that sentence.

Now, looking at the screen, I noticed that the text was lagging in LibreOffice Writer and that Microsoft 10’s ‘circle of death’ was spinning right before the screen flickered again.

“Great”, I thought, “I get to be distracted by Microsoft Windows Shenanigans again.”

I brought up the task manager (I call it the task mangler) and waited. There went the flicker again after the circle of death. The task manager also flickered and that would indicate that the problem was likely a video driver.

I had officially changed from writer to troubleshooter at this point, having completely lost my original train of thought. I’d allowed Microsoft to do it’s annoying update fairly recently, so I went through the process of reading up on the changes in their Knowledge Base, written by a group of people who have no business writing any sort of documentation. That seemed clear.

And so then I checked to make sure the drivers were up to date, which required a password I’d forgotten because I use the PIN. So suddenly I’m trying to solve that problem while Windows is trying to tell me to update something else. I updated again, per their suggestion.

The flicker remained. It even seemed to worsen. It could have been my patience steaming out of my ears in having to deal with this, and I thought very dark thoughts about people in Redmond, Washington. Very dark thoughts indeed, thoughts that I will not write here because someone might take it seriously enough to send a team to come have a chat with me. I kid, I kid! Maybe!

I’d been doing the web browsing for some of the troubleshooting on my phone because that screen didn’t flicker, and I was about to go back to writing on a separate machine – the Apple I have stashed in another room, whose keys don’t travel the way I like. I visited the bathroom and switched on the light when I saw that there was a phase issue. The light flickered.

Suddenly it all fell into place. I checked my phone’s WhatsApp at 4:39 pm to see that there had been another phase issue on the compound for an hour.

My laptop was acting out because it thought that electricity was disconnecting and reconnecting through the surge protectors. I had recalled noticing the battery charging showing up in the lower right from time to time but since I was hyperfocused on a particular branch of troubleshooting, I had completely missed the basics.

I had forgotten where I lived – Trinidad and Tobago – and I had forgotten the compound had been suffering phase issues since they closed down the main power station in the area, PowerGen, some time ago. Since around that time, we’ve had phase issues at Victoria Keyes, which I wrote to Trinidad and Tobago Electricity Commission (T&TEC) about to not avail.

The WhatsApp chat was useless, filled with things that I had responded to and answered over the course of the last 3 years about what happens on the compound when we have phase issues. It’s one of the reasons I ignore the chat; I hate repeating myself and I often feel the need to explain things to people who explanations bounce off of, despite my best efforts in trying different ways to communicate it. Electricity, as common as it is, confounds people.

I took a break, T&TEC sent a truck, they reset a fuse on a local transformer and I thought to myself that they really need to deal with this consistent problem again. One of the people applauded the T&TEC response time, which was stellar, but… we keep having the same issue over and over again.

So – I was troubleshooting the wrong thing to start with, and because I find the signal to noise ratio of the chats at Victoria Keyes inordinately low, I ignored them. I spent an hour chasing the wrong problem and, had I simply remembered where I lived. In a country where even water is an issue because everyone likes to kick the can down the road, which impacted my community up until a few days ago.

Microsoft’s off the hook. Poor governance and government run enterprises, through a shell game of government owned corporations, struck again.

When troubleshooting, the first step is to check your instruments. In Trinidad and Tobago, it also means checking the quality of your electrical connection. Fortunately, computers don’t require water, so we don’t have to have that in the troubleshooting guide.

There. I feel better now.

To Err Is Not Just Human.

~ Taran ~ Leave a comment

When I saw that only only 40% of People Can Identify Bots from Humans, I wasn’t too surprised. We like to think that technology is getting smarter, but… well… there are other things that are related that we shouldn’t be too quick to discount.

…Children are taught to regurgitate what others tell them and to rely on digital assistants to curate the world rather than learn to navigate the informational landscape on their own. Schools no longer teach source triangulation, conflict arbitration, separating fact from opinion, citation chaining, conducting research or even the basic concept of verification and validation. In short, we’ve stopped teaching society how to think about information, leaving our citizenry adrift in the digital wilderness increasingly saturated with falsehoods without so much as a compass or map to help them find their way to safety. The solution is to teach the world’s citizenry the basics of information literacy…

Kalev Leetaru, “A Reminder That ‘Fake News’ Is An Information Literacy Problem – Not A Technology Problem“, Forbes.com, July 7th, 2019.

Couple that with the study that showed the average attention span is now 47 seconds, there’s a lot of forgiveness for an effective Turing test these days. The very idea of the Turing test did not come up in a world where people thought the world was flat, and that was almost 75 years ago. No one was eating Tide Pods, either, though I do believe that’s under control now.

…Researchers were aware that these tactics might be deployed, so they specifically trained their bots to strategically utilize typos and other forms of errors in syntax and grammar to make them seem more human. Personal questions were also used fairly frequently, with participants trying to get the bots to talk about their backgrounds, assuming that bots would not be able to respond to such queries.

Once again, these bots were trained on datasets that included a wide range of personal stories, and that led to them being able to answer these questions in a way that is surprisingly similar to human beings. Hence, 32% of participants were unable to successfully identity AI during this experiment with all things having been considered and taken into account…

Zia Muhammad, “Only 40% of People Can Identify Bots from Humans“, Digital Information World, July 11th, 2023.

So what they did is they made the bots make mistakes on purpose so that they could fool humans better, because human typos and the inability to write properly are hallmarks of being human.

To err is bot.

Bias, Color, and Stereotypes Shown by Buzzfeed.

~ Taran ~ 3 Comments

Buzzfeed had a post last week that I thought I’d let soak for the comments before I wrote anything about it. The image at top are 4 images from their post, made much smaller to create one image for this one. The intent is to have the examples without the quality, which you can see on their post – all 50 of them.

I noticed a few things right off the bat in the images in, “I Asked AI What Europeans Think Americans From Every Single State Look Like, And The Results Are Just Plain Mean“, and it’s almost like a Norman Rockwell caricature of each state.

Two of the states are likely easily identifiable by most Americans, 2 maybe not. As an American, Louisiana and Idaho are pretty easy. What are the other two? Go see the Buzzfeed post.

Not all of them are that bad. However, there are only people of European descent in the images. They do seem pretty consistent about how the United States has portrayed itself in some ways. I also admire that the author had the time to work in 50 states. I find even the thought of doing that boring.

The comments, though, are pretty interesting to read.

The first comment in this thread is that the artificial intelligence doesn’t think ‘people of color’ exist… yet the first reply to that is that it’s ‘anti-white for sure’. We live in a world when both perspectives aren’t necessarily wrong.

Is this the trouble with AI and bias? Or is it the trouble with us and bias?

I’ll offer it’s both.

Why aren’t there people of non-European descent in there? I have no idea. I have some ideas.

For example, between the 1940s and 1990s, physical film was biased itself.

Since many images are scanned images, and not all images of darker skin tones are flattering – National Geographic is probably the only magazine of that era that seemed to work on it more resolutely – I don’t think that images from that period would not be biased.

Then, there’s the media bias. When I looked at what Buzzfeed’s generated image for Florida (it’s one of the 4 in the top), I could swear I had met that guy somewhere. He’s an amalgamation of many people I have known over the years, and not in a bad way at all.

What other reasons would there be? Well, if you were to ask me about stereotypes by state of ‘people of color’, I couldn’t come up with one. There are differences, of course, but they aren’t as apparent.

Not one Native American in the bunch. New Mexico, though, does seem to represent aliens.

The bias may also be because of what Europeans normally see of America, and that can be an issue of (1) What Europeans want to see, (2) What media portrays, and (3) What is true.

How artificial intelligences see us, though, might be more interesting to ask them. If you describe yourself to an artificial intelligence, I believe the further you are from the norm of the data, the more descriptive you’ll have to be.

AI’s are just systems, and not very smart ones right now. Perhaps we should watch what we feed them, but we haven’t been very good at what we feed ourselves, so I’m not sure how we should proceed.

Firing Up Recommendations: Pyrorank.

~ Taran ~ 1 Comment

Being a bit busy with other things, I didn’t get to write a little but about a new recommendation algorithm which involves artificial intelligence: Pyrorank. It has some lofty claims, largely hidden by academia and academic verbiage.

I initially read about it in Researchers devise algorithm to break through ‘search bubbles’ on July 10th and put it into the stack of things I consider interesting. ‘Search’ and ‘Bubbles’ mean something to some of us who, in the days of antiquity, wrote our own search and sort algorithms from scratch.

What this new algorithm is claimed to do is give you better recommendations by “reducing the impact of users’ profiles and broadening recommendations that still reflect the focus of the search, producing more diverse and useful results.”

In other words, recommendations on Netflix, or Amazon.com, or even advertising on Facebook could be less annoyingly predictable, showing us the same things – some of which we may have already seen, purchased, or passed over before. Personally, it wasn’t long before I started seeing present recommendation algorithms as a tyranny, and with my eclectic tastes that can be supremely annoying.

Recommendation systems, used by Google, Netflix, and Spotify, among others, are algorithms that use data to suggest or recommend products or choices to consumers based on the users’ past purchases, search history, and demographics. However, these parameters bias search outcomes because they put users in filter bubbles.

“The traditional way recommendation systems work is by basing recommendations on the notion of similarity,” explains Bari, who leads the Courant Institute’s Predictive Analytics and AI Research Lab. “This means that you will see similar items in the choice and recommended lists based on either users similar to you or similar items you have bought. For instance, if I am an Apple product user, I will increasingly see more and more Apple products in my recommendations.”

The limitations of existing recommendation systems have become evident in striking ways. For instance, political partisans may be largely directed to news content that aligns with their pre-existing views. More significantly, recommender systems have turned up self-harm videos to susceptible individuals.

Researchers devise algorithm to break through ‘search bubbles‘, New York University, 10 July 2023.

This sounds hopeful, particularly for social media algorithms which we have seen have reinforced polarized views. It could increase the size of the echo chambers (there are always echo chambers) while adding diversity to them.

Thus I did some digging this morning and found this paper, “Pyrorank: A Novel Nature-Inspired Algorithm to Promote Diversity in Recommender Systems“, which is unfortunately paywalled. I have requested the full text, and if I do manage to get it and I do find anything particularly interesting in it, I’ll post a bit more on it.

I also looked for different perspectives on it; others would have looked at the paper and found different things worth highlighting. My focus was on how it actually compares.

A comparison was made between Pyrorank and the traditional recommendation system to test the viability of each system. This experiment was carried out on large Movielens, Good Books, and Goodreads datasets. The objective of the testing was to find out which system stays true to the purpose of accurate recommendations while simultaneously providing diversification and unrepeated results.

The results were hugely in favor of Pyrorank, which not only stuck to genuine core recommendations but also gave mixed results that did not align with the past results of product purchases or to someone who is a similar user.

Pyrorank – A New Pathway For Your Search Engine, DigitalWorld, Web Desk, Wednesday, July 12, 2023

Unfortunately, it doesn’t say how rigorous the testing was, but it does sound a little promising.

What is interesting is that this is based on pyrodiversity, which is something that I had never considered, so to me this is a little new and exciting – once it lives up to it’s claimed results.

There may be hope for recommendations yet.

Singularity Summary

~ Taran ~ 2 Comments

The last few days I’ve spent an inordinate amount of time reading a lot about different aspects of the technological singularity. I wrote about it in the context of just the technology aspect, as well as what I found related to the other human aspects.

My summary is this.

By definition, we’ll never be ready for a technological singularity, and this should be a concern. While Caribbean leaders talk about fake eyelashes causing crime, which on it’s surface is amusing but has less humorous meaning, there are deeper issues we as a species have across the globe and into our fledgling attempts to go into space.

With the latest issues related to tourism to dark places where you can’t really see anything, where the haves are spending more than the have nots see sometimes in a lifetime so that the have nots end up paying taxes to find out what happened, there’s a clear issue of economic disparity that does not mesh well with measurements of global poverty, where economic disparity is climbing while global poverty is said to be going down.

We’re still fighting this made up concept of race in ways that divide us more than connect us, even as everyone seems to have a laser pointer trying to drag our attention one way or the other. We have wars being fought – real wars – for economic reasons in a time when loud politicians clamor that there’s nothing to worry about when it comes to the economy. We have people having control over other people’s bodies. All of these things are being magnified and polarized through the technologies of social media.

I’d say that before we worry too much about a technological singularity, we should be focusing ourselves on the systems that continue failing the world as a whole.

For now, I’ll put this topic to bed, tucked in with duct tape and leather restraints. Our progress as a species is not measured by technology alone, and I think perhaps now that should be our focus. Artificial intelligence as it is might actually be able to help us with these things, but it has to be carefully done.

It may already be too late for that, but it’s not as if there are many options.

The Technological Singularity: A Roundup of Perspectives Outside Tech.

~ Taran ~ 2 Comments

Yesterday I wrote about the technological singularity as espoused by positive singulitarians that are sharing their perspectives on such a singularity – and rebutted some of the problems with the laser pointer that they want us to focus on. Fairly or unfairly, they quote Ray Kurzweil a lot.

Generally speaking, they are in the artificial intelligence business and therefore they want to sell us a future as they have done in the past, much like the paperless office as I mentioned here.

There’s more to humanity than that, I would like to think, so I’d been reading up and considering other aspects of humanity that may have some things to say that are of weight to the context of the hypothetical technological singularity. I write ‘hypotherical‘ because any prediction is hypothetical, even when you’re tilting with marketing to assure it happens.

Yesterday, I got a little sidetracked with the issue of global economic disparity versus global poverty, which I’ve resolved not to solve because I don’t think it is meant to be solved or an economist would have already.

However, I found much that is being said outside the realms of the more pure technologists.

…The time for international political action has therefore arrived. Both AI-producer and non-AI-producer countries must come together to create an international organism of technological oversight, along with an international treaty in artificial intelligence setting forth basic ethical principles.   

The greatest risk of all is that humans might realize that AI singularity has taken place only when machines remove from their learning adaptations the flaw of their original design limiting their intelligence: human input. After all, AI singularity will be irreversible once machines realize what humans often forget: to err is human. 

“Entering the singularity: Has AI reached the point of no return?“, The Hill (Technology, Opinion), by J. Mauricio Gaona , Opinion Contributor – 05/15/23

That is, of course, a major issue. Garbage in, garbage out. If you want less errors, every software engineer of worth knows that you want to minimize the capacity of the user to create more errors. That’s a logical thing to point out.

Psychology Today had an impressively balanced article, well worth the read.

“…What does worry me is a “second singularity.”

The second singularity is not just about computers getting more powerful, which they are, but the simultaneous reduction in expertise that we are seeing in many quarters. As organizations outsource decision making authority to machines, workers will have fewer opportunities to get smarter, which just encourages more outsourcing.

The second singularity is actually much closer to us in time than Kurzweil’s original notion of a singularity. It is a second singularity in deference to Kurzweil’s analysis, rather than for chronological reasons…”

“The Second Singularity: Human expertise and the rise of AI.“, Gary Klein PhD, Psychology Today, December 3rd, 2019.

Given that the article is three and a half years old, it’s impressively descriptive and poignant for the conversation today, delving into nuanced points about expertise – some things are worth losing, some not. More people should read that article, it’s a fairly short read and well written, including suggestions on what we should do even now. It has definitely aged well.

Moving on, we get to an aspect of the economic perspective. An article on Forbes has some interesting questions, condensed below.

… how will the potential of bioengineering capabilities re-define and re-design the way we produce raw materials?…

…how will the emerging potential of molecular manufacturing and self-replicating systems reverse the very process of globalization, as nations who own and control this technology will not need other nations as they can produce/manufacture anything they need or want in unlimited quantities?…

…How will blockchain based additive manufacturing create a participatory economy blurring the boundaries of national geography? How will a nation’s economy be influenced by digital manufacturing designs from anywhere and anyone?…

…How will nations deal with the likely collapse of the economic system in the coming years? Are they prepared?…

“The End Of Work: The Consequences Of An Economic Singularity“, Jayshree Pandya (née Bhatt), Ph.D., Forbes>Innovation>AI, Feb 17, 2019

Another article that has aged well at over 4 years old, because those questions are still to be answered. Interestingly, the author also mentions Risk Group LLC, where she is the CEO. The article lists her as a former contributor, and her author page on Forbes describes her as, “working passionately to define a new security centric operating system for humanity. Her efforts towards building a strategic security risk intelligence platform are to equip the global strategic security community with the tools and culture to collectively imagine the strategic security risks to our future and to define and design a new security centric operating system for the future of humanity.”

Definitely an interesting person, and in 2019 it seems she was well aware of the challenges.

“…The shape the future of humanity takes will be the result of complex, changing, challenging and competing for technological, political, social and economic forces. While some of these forces are known, there is a lot that is still not known and the speed at which the unknowns can unfold is difficult to predict. But unless we make a strong effort to make the unknowns, known, the outcome of this emerging battle between technological singularity and economic singularity seems to be just the beginning of social unrest and turmoil…”

“The End Of Work: The Consequences Of An Economic Singularity“, Jayshree Pandya (née Bhatt), Ph.D., Forbes>Innovation>AI, Feb 17, 2019

It’s a shame Forbes paywalls their content, or more of us might have read it when it was written. This sort of article definitely needed a wider audience in 2019, I think.

Just a glance at RiskGroup LLC’s work makes it look like they have been busily working on these things. I’ll be looking their stuff over for the next few days, I expect.

In an interesting context of education and sociology, I came across an article that quotes Ethan Mollick, associate professor at the Wharton School at the University of Pennsylvania:

“The nature of jobs just changed fundamentally. The nature of how we educate, the nature of how teachers and students relate to work, all that has just changed too. Even if there’s no advancement in AI after today, that’s already happened,” said Mollick, an economic sociologist who studies and teaches innovation and entrepreneurship at Wharton.

“We are seeing, in controlled studies, improvements in performance for people doing job tasks with AI of between 20% and 80%. We’ve never seen numbers like that. The steam engine was 25%.”

“Has new AI catapulted past singularity into unpredictability?“, Karen McGregor, University World News, 27 April 2023.

Things have been changing rapidly indeed. The PC Revolution was relatively slow, the Internet sped things up and then the mobile devices took things to a higher level. The comparison to the steam engine is pretty interesting.

Lastly, I’ll leave you with an anthropological paper that I found. It’s a lengthy read, so I’ll just put the abstract below and let you follow the link. It gets into collective consciousness.

The technological singularity is popularly envisioned as a point in time when (a) an explosion of growth in artificial intelligence (AI) leads to machines becoming smarter than humans in every capacity, even gaining consciousness in the process; or (b) humans become so integrated with AI that we could no longer be called human in the traditional sense. This article argues that the technological singularity does not represent a point in time but a process in the ongoing construction of a collective consciousness. Innovations from the earliest graphic representations to the present reduced the time it took to transmit information, reducing the cognitive space between individuals. The steady pace of innovations ultimately led to the communications satellite, fast-tracking this collective consciousness. The development of AI in the late 1960s has been the latest innovation in this process, increasing the speed of information while allowing individuals to shape events as they happen.

O’Lemmon, M. (2020). The Technological Singularity as the Emergence of a Collective Consciousness: An Anthropological Perspective. Bulletin of Science, Technology & Society, 40(1–2), 15–27. https://doi.org/10.1177/0270467620981000

That’s from 2020. Thus, most of the things I’ve found have been related to present issues yet were written some time ago, hidden in the silos of specialties beyond that of just technology.

There’s definitely a lot of food for thought out there when you cast a wider net beyond technologists.

It might be nice to get a better roundup, but I do have other writing I’m supposed to be working on.