big data

Social Networks, Privacy, Revenue and AI.

~ Taran ~ 1 Comment

I’ve seen more and more people leaving Facebook because their content just isn’t getting into timelines. It’s an interesting thing to consider the possibilities of. While some of the complaints about the Facebook algorithms are fun to read, it doesn’t really mean too much to write those sort of complaints. It’s not as if Facebook is going to change it’s algorithms over complaints.

As I pointed out to people, people using Facebook aren’t the customers. People using Twitter-X aren’t the customers either. To be a customer, you have to buy something. Who buys things on social networks? Advertisers are one, of course.

That’s something Elon Musk didn’t quite get the memo on. Why would he be this confidence? Hubris? Maybe, that always seems a factor, but it’s probably something more sensible.

Billionaires used to be much better spoken, it seems.

There’s something pretty valuable in social networks that people don’t see. It’s the user data, which is strangely what the canceled West World was about. The real value is in being able to predict what people want and influence outcomes, much as the television series showed after the first season.1

Many people seem to think that privacy is only about credit card information and personal details. It also includes choices that allow algorithms to predict choices. Humans are black boxes in this regard, and if you have enough computing power you can go around poking and prodding to see the results.

Have you noticed that these social networks are linked somehow to AI initiatives? Through Meta, Facebook is linked to AI initiatives of Meta. Musk, chief twit at X, has his fingers in the AI pie too.

Artificial intelligences need learning models, and if you own a social network, you not only get to poke and prod – you have the potential to influence. Are your future choices something that fall under privacy? Probably not – but your past choices probably should be because that’s how you get to predicting and influencing future choices.

I never really got into Twitter. Facebook was less interruptive. On the surface, these started off as content management systems that provided a service and had paid advertising to support it, yet now one has to wonder at the value of the user data. Back in 2018, Cambridge Analytics harvested data from 50 million Facebook users. Zuckerberg later apologized, and talked about how 3rd party apps would be limited. To his credit, I think it was handled pretty well.

Still, it also signaled how powerful and useful that data could be and if you own a social network, that would at least give you pause. After all, Cambridge Analytics influenced politics at the least, and that could have also influenced markets. The butterfly effect reins supreme in the age of big data and artificial intelligence.

This is why privacy is important in the age of artificial intelligence learning models, algorithms, and so forth. It can impact the responses one gets from any large language model, which is why there are pretty serious questions regarding privacy, copyright, and other things related to training them. Bias leaks into everything, and popular bias on social networks is simply about the most vocal and repetitive – not about what is actually correct. This is also why canceling as a culture phenomenon can also be so damaging. It’s a nuclear option in the world of information, and oddly, large groups of smart or stupid people can use it with impunity.

This is why we see large language models hedge on some questions presently, because of conflicts within the learning model as well as some well designed algorithms. In that we should be a little grateful.

We should probably lobbying to find out what is in these learning models that artificial intelligences are given in much the same way we used2 to grill people who would represent us collectively. Sure, Elon Musk might be taking a financial hit, but what if it’s a gambit to leverage user data for bigger returns later with his ethics embedded in how he gets his companies to do that?

You don’t have to like or dislike people to question them and how they use this data, but we should all be a bit concerned. Yes, artificial intelligence is pretty cool and interesting, but unleashed without question of the integrity of the information trained on is at the least foolish.

Be careful what you share, what you say, who you interact with and why. Quizzes that require access to your user profile are definitely questionable, as that information and information of people you are connected with quickly get folded into data creating a digital shadow of yourself, part of the larger crowd that can influence the now and the future.

  1. This is not to say it was canceled for this reason. I only recently watched it, and have yet to finish season 3, but it’s very compelling and topical content for the now. Great writing and acting. ↩︎
  2. We don’t seem to be that good at it grilling people these days, perhaps because of all of this and more. ↩︎

Trinidad and Tobago and/vs AI.

~ Taran ~ 2 Comments

When I wrote ‘Artificial Extinction‘, I briefly touched on coverage related to artificial intelligence here in Trinidad and Tobago. It’s hard to explain just how out of mind it is, so I’ll just write a bit of the local scene.

Today, as I stood in line waiting an annoying amount of time waiting to pay for the 5l bottle of water at a local convenience store, I glanced at the headlines. As usual, there was someone having trouble with something at the head of the line, the other register was closed, and the line formed.

One of the benefits of that line is that I get to run my eyes across the front pages of the local newspapers: Newsday, Trinidad Express and Trinidad Guardian.

The Rastafarian gentleman in front of me found something of interest in the Trinidad Express. I saw something about the need for Constitutional Reform, a picture of “Indian Arrival Day Stalwarts”, ‘Paradise in Peril’ and a plea from the mother of a kidnapping victim. Having been back and forth over the decades, the news seems to say the same with only names changing. The politicians play politics, the crime has spiraled so long that it is now in control of the criminals, and nobody has fresh ideas. They all seem to be foreign and abused ideas, much like some of the used cars you can buy from Japan.

This is the canvas upon which local news is painted daily. I thought about seeing Trinidad and Tobago represented on Planet Earth (Episode 6) through Grand Riviere Village’s volunteer work to assist and protect the leatherback turtles. when I did a web search, I found the leatherback turtle site offline (something I’m considering digging into). That’s a shame. Keeping a website online for something with international attention seems important.

I get home, walking past the condo’s office, I wave briefly at the administrator who was busy talking with someone. 15 years as a corporate secretary, retired, decades of experience that could soon be replaced with something purchased off the shelf. The latent thought of my own experience being replaced looms quietly in the background as I enter the elevator, my thoughts on how to connect the local perspective on technology and thus artificial intelligence to the larger global perspective of “this could end very badly“.

My friends and neighbors are more worried about their family’s security than some online application spitting out gobs of text when asked a question. In a land where there are no questions, no one needs an oracle. The economic diversity of Trinidad and Tobago is simply not there, the oil money stolen or squandered (or both), and the youths see increasingly little opportunity outside of crime, as we talked about while I was at the barber shop last week.

Artificial intelligence is not going to help with these things, because these are largely broken systems that those who profit from do not want to fix. ChatGPT can go blue in the face telling the politicians what they should do. They’ve been told what it has to offer thousands of times before over the decades. The faces largely have not changed, only grown older and in one case distinctly more cadaverous.

Years ago, I had a Minister message me once because something I wrote, and he asked where I got the data from – I cited the source that he should have been aware of, the open data portal of Trinidad and Tobago. He was agog. He’d been asking for that information for over a year and no one seemed to know where it was. The website has since been updated, the data not so much.

Meanwhile, the largest employer in Trinidad and Tobago is the government, where many good people participate in overcomplicated wheels of bureaucracy. We could use technology to replace much of that, but then where would the people work? And since they vote, who would they vote for if they lose their jobs?

With this context, now, I can now discuss AI in Trinidad and Tobago in the context of jobs, particularly the last 3 paragraphs:

“…Taking charge of this rapidly evolving scenario of workplace change will demand one fundamental and overdue evolution in governance, the continuous gathering and distribution of actionable information about how this country operates.

It was a note that Jonathan Cumberbatch, Assistant VP, Human Resources and Administration at UTT touched on cautiously when he noted that, “Data drives most of the conversation outside of TT, but we don’t have a sense of that in TT.”

The propensity of governance to proceed on feelings, hunches and political expedience might have worked in the past, but the national distaste for transparently gathered, publicly available information cannot continue into an era hallmarked by a reliance on reliable, continuously updated datasets.”

“AI and your job“, Mark Lyndersay, TechNewsTT and BitDepth#1408 for May 29, 2023

Of course, it wasn’t a global roundup of people related to AI, just those with local interests talking to the local Chamber of Commerce related to their products. Microsoft was definitely there, others… not here.

The short answer is that Trinidad and Tobago isn’t ready. Neither is most of the rest of the world, which is why there’s concern by some. I’ve seen firsthand government offices and even business offices completely ignore data driven approaches. Just recently, I proposed starting with the basics in the condo’s office, only to hear that without actual data they’re just pushing forward into a ticket system to solve all the problems. In time they will find it creates new ones, but that will be another story.

The point is that if you can’t even do data driven stuff, keep a volunteer website up when there’s international attention, the wave of artificial intelligence that will drive the world economy will leave many people stranded on islands, perhaps even twin island Republics. What will be done about this?

Maybe they’ll talk about it in Parliament. Then, if history repeats itself, nothing will happen.

Or, things could change. Things definitely should change, but those changes need to happen faster and faster as the government slides into the Pitch Lake, dragging it’s citizens with it. .

The Reading Problem.

~ Taran ~ 1 Comment

Reading enlightensWe’ve all encountered it. We post an article on some social network and someone comments without reading the article, or not reading it properly.

As someone who writes, I went through the stages of grief about it. I can apathetically report that I don’t care as much as I used to about it. Many people tend to skim headlines, sharing them without thought, and then blaming the Russians or whoever the headline targets for everything.

As someone who reads, I’m confounded by it. When I read that skim reading is the new reading, some of it began to make sense:

…As work in neurosciences indicates, the acquisition of literacy necessitated a new circuit in our species’ brain more than 6,000 years ago. That circuit evolved from a very simple mechanism for decoding basic information, like the number of goats in one’s herd, to the present, highly elaborated reading brain. My research depicts how the present reading brain enables the development of some of our most important intellectual and affective processes: internalized knowledge, analogical reasoning, and inference; perspective-taking and empathy; critical analysis and the generation of insight. Research surfacing in many parts of the world now cautions that each of these essential “deep reading” processes may be under threat as we move into digital-based modes of reading… — 

The bad news is that anyone who read that didn’t skim it, and therefore doesn’t need to understand it on a personal level. The good news is that there are people thinking about it.

But there are other things, things that also need to be addressed. Some people don’t even skim articles, they skim headlines – and in a rush, for whatever reason, they share it. Before you know it, things with no actual truth to them, or just enough to be shared, inundate the entire web.

Issues, too, of framing with technology come into context.

And what it really boils down to is that, aside from how much we might like to think people who are demonstrably susceptible to all of this are ignorant, as a society we generate a lot of things to read. Publishers understand the need for sticky headlines and ‘cover art’, and are good at it.

People don’t have enough time to deep read things, and they don’t want to be left out of an accelerating world – but are proud of themselves when they can type out the 4 letters, ‘TLDR’.

People who figured all of this out long ago have capitalized on it. Fake News, coupled with Big Data analysis of what people are interested in, allows some impressive amount of sharing of information that should probably be tossed in a pyre of literacy.

So, what to do as a writer? Well, the answer to that is simple: Keep writing.

And, as a global citizen on the Internet? Deep read. Don’t skim. Encourage others to do it.

 

Information Fiefdoms

~ Taran ~ 2 Comments

Social Media Information OverloadYesterday, I found myself standing in Nigel Khan’s bookstore in Southpark, looking at what I consider old books.

I have a habit when I look at books, something I picked up in Trinidad some years ago after the Internet became more than a novelty. I check the date a book was published. It keeps me from buying antiques, though I have also been known to buy books in thrift shops abroad (though I am very picky).

I found myself looking at Tim Wu’s ‘The Master Switch: The Rise and Fall of Information Empires‘. Given some of the stuff I’d been talking about in different circles, it interested me – and Tim Wu I knew from his work with Network Neutrality. I checked the publication date.

November, 2010.
It’s August, 2018.

8 years. 5.33 evolutions of Moore’s Law, which is unfair since it isn’t a technology book – but it’s an indicator. Things change quickly. Information empires rise and fall in less time these days – someone was celebrating integrating something with OneNote in one of the groups I participate in, thinking that he’d finally gotten things on track – when, in fact, it’s just a snapshot more subject to Moore’s Law than anyone cares admit – except for the people who want to sell you more hardware and more software. They’ve evolved to the subscription model to make their financial flow rates more consistent, while you, dear subscriber, don’t actually own anything you subscribe to.

You’re building a house with everything on loan from the hardware store. When your subscription is up, the house disappears.

Information empires indeed. Your information may be your own, but how you get to it is controlled by someone who might not be there tomorrow.

We tend to think of information in very limited ways when we are in fact surrounded by it. We are information. From our DNA to our fingerprints, from our ears to our hair follicles – we are information, information that moves around and interacts with other information. We still haven’t figured out our brains, a depressing fact since it seems a few of us have them, but there we have it.

Information empires. What separates data from information is only really one thing – being used. Data sits there; it’s a scalar. Information is a vector – and really, information has more than one vector. Your mother is only a mother to you – she might be an aunt to someone else, a boss to someone else, an employee to someone else, and a daughter to your grandmother. Information allows context, and there’s more than one context.

If you’re fortunate, you see at least one tree a day. That tree says a lot, and you may not know it. Some trees need a lot of water, some don’t. Some require rich soil, some don’t. Simply by existing, it tells us about the environment it is in. Information surrounds us.

Yet we tend to think of information in the context of libraries, or of database tables. And we tend to look at Information Empires – be they by copyright, by access (Net Neutrality, digital divide, et al), or simply because of incompatible technologies. They come and go, increasingly not entering the public domain, increasingly lost – perhaps sometimes for good.

And if you go outside right now and stand, breathing the air, feeling the wind, watching the foliage shift left and right, you are awash in information that you take for granted – an empire older than we are, information going between plants through fungus.

There are truly no information empires in humanity other than those that are protected by laws. These are fiefdoms, gatekeepers to information.

The information empire – there is only one – surrounds us.

Technology and Mediation

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Open source photography -- are you in or out?As I mentioned before, I recently took a level 1 mediation course and in doing that, I began looking at many things through a new lens. It’s a process, and since it’s my life, much of what I’ve looked at relates to technology.

Looking through such a lens, though, reveals a mess.

Nature, Tech and Mediation

When we think of technology these days, we tend to think of the Internet related technologies, technologies that through our lifetime have run through our lives like fire – seemingly unstoppable, without an ability to individually control them and how they impact our lives. This is because fire, like the wheel and other technologies like them, are based on natural laws. There is no control over natural laws, there is only an understanding of them and use of that understanding.

For a successful technology, reality must take precedence over public relations, for Nature cannot be fooled.
– Richard P. Feynman, Appendix F of the Rogers Commission Report (on the Challenger disaster).

With Internet technologies, though, it’s not so much about nature because, while the platform is derived from natural laws, what is used on them is defined by human minds. By code, and what that code works on: our content.

The Code

Why does code work the way it does? It’s typically consensus of the group involved with writing it, which varies. The Open Source and Free Software communities have a meritocracy structure, and proprietary approaches tend to a more corporate structure. The ‘object oriented’ approach means code gets re-used, which means that it becomes something plugged into applications it may not originally be designed for – and because it works for the criteria of the project.

Just because something works for the criteria of a project, though, doesn’t mean it’s the best fit – something I’ve seen all too many times. And the criteria of the project are almost never complete; when you set code out in the wild of the world subject to users, their interactions can take projects down paths one never expected.

In this way, code and fire are similar. Software Engineers and companies like to think that they have everything thought out, but we typically miss something as we chase a deadline or the deadline chases us. And this is where that similarity with fire disappears: the code evolves, or the project dies.

In all of this, where does mediation happen? Absolutely nowhere. Any piece of code is a balance of negotiations between what the developers think the consumers want, the timeline, and whatever the company or open source community decides …and nowadays, what the company and the open source community decide.

The end users, the consumers, the majority of people, really don’t have too much of a say in any of this. There is one methodology that forces consumer interaction more than others (DevOps), but it’s only for more finite projects and even then is a negotiation with an opportunity of mediation that I have never seen or heard of happening.

“You get what we write.” – every software company, ever, til they get sold or closed.

The Content

The Internet evolved and continues to evolve because of the complexity of the platform allows it to. While we tend to think we have control over this, it has encircled smaller communities without it, raging like a wildfire. A lot of that has to do with content.

When it comes to content there’s no true mediation, either – my last entry on journalism and social media points to people deciding to mediate – to actively listen, to actively summarize, and to be neutral. Of course, that’s all silly because humans aren’t very good at that. As a society, we’re happier with 30 minutes of silly people screaming at each other over non-issues than we are with a 2 hour documentary on why silly people scream at each other. It boggles the rational mind, but there it is. Our technology has outstripped us in this regard.

A controversial blog post with a catchy title will be shared across social media even if it’s completely wrong. Statistically, the people who share actual scientific research is pretty slim – but the people who share opinions on such things is devastatingly large. There is a happiness people find in this conflict that baffles the calm mind.

So, all this content is out there – generating money, having political importance, allegedly influencing elections (another thing to have an opinion on) – and that drives the underlying technology, both hardware and software.

Hardware, for the most part, simply makes things possible and makes things faster. Software gets more and more bloated as software manufacturers make it easier to write code within their own frameworks – nothing beyond the box is encouraged. Thinking inside the box is where the majority of developers now live, depending on a framework to make a living.

There’s just no mediation here.

And the question arises whether there should be.

 

Of Digital Shadows And Digital Ghosts

~ Taran ~ 4 Comments

Ice, Shadow and StoneIn writing about shadows and ghosts, it’s hard not to draw the line to how we process data – the phrase big data gets tossed around a lot in this way.

Data Science allows us to create constructs of data – interpreted and derived, insinuated and insulated, when in fact we know about as much about that data as we do the people in our own lives – typically insufficient to understand them as people, something I alluded to here.

Data only tells us what has happened, it doesn’t tell us what will happen, and it’s completely based on the availability we frame in and from data. We can create shadows from that data, but the real value of data is in the ghosts – the collected data in contexts beyond our frames and availability.

This is the implicit flaw in machine learning and even some types of AI. It’s where ethics intersects technology when the technologies have the capacity to affect human lives for better and worse, because it becomes a problem of whether it’s fair.

And we really aren’t very good at ‘fair’.

The Networking of Truth And Falsehood: ‘Fake News’

~ Taran ~ 3 Comments

MissionThere is an incessant debate over truth right now, the same as there ever is, branded this time as ‘fake news’.

It has everyone mistrusting everyone, everything – everyone but the least ethically or cognitively competent, willful or not. It’s the elephant on the chest of social media companies, traditional media companies fighting for business relevancy in a networked world, and we, the factually impaired.

In all of this, we focus on the lack of truth. Yet, where we find truth we find precision, and where we find precision, we find error. When we talk about fake news, we’re really talking about the innocuous stories fed to the media – social and traditional – that spread not because they’re good, but because they’re catchy. ‘Sticky’, as marketers would say.

The Basics

Truth itself is a fickle thing. We seek objectivity in our subjective experiences of life, and only when we master these subjectivities do we diminish error and improve the precision. Again, where we experience precision, we experience error – they cannot exist without each other.

There are seconds of truth.
There are minutes of truth.
There are degrees of truth.

It’s all trigonometry to an extent, which fuzzy logic measures by weight, but it’s there – particularly when reconciling two versions of the truth. When we get three versions of the truth, it gets more complicated. When we get 10 versions of the truth, it’s even more exponentially complicated. So we do what humans do – we simplify when we’re overwhelmed. When we’re scared, it might become about race or about people ‘over there’, a wide net that catches innocent and guilty simply to catch the guilty.

Aggregating Truth

All of this used to be more manageable when we had fewer versions of the truth. The Internet came along and gave us the metaphorical 10,000 monkeys typing out their own versions of Shakespeare all over the Internet. Most monkeys simply regurgitate the same stuff they read somewhere else, hoping to make their audience click around their site to get a little bit more advertising revenue. When you drill down, there are actually very few monkeys that come up with the best versions and they’re not the same all the time.

But the monkeys that come up with the most popular versions aren’t necessarily the best – and the best versions are not always popular. Network powered societies amplify this and we’re network powered, so much so we cannot truly conceive versions of truth as easily. Facts have become croutons on a low carb salad – almost extinct, if not extinct.

And it all happens faster. Where we might have gotten news once a day with the printing press, twice a day with the television, thrice with the radio, we have versions of truth on tap 24/7, where the first to cover something gets the prized advertising revenue no matter how uninformative and perhaps wrong the coverage is.

Because we simplify. It’s human nature. We ’round off’. We estimate. We guess. We find comfort in opinions and op-eds that get more clicks with less facts. And those that want to insert stories to spread can get their research done through aggregate data mined from social networks and your local grocery store.

We find in life that when the people around us make better decisions, we ourselves get better choices. We find that when we make better decisions, those around us get better choices.

And we find that the opposite is also true.

Rethink where you get your content. Re-assess your connections in what they share, reassess what you read and if none of it makes you uncomfortable, you’re not reading facts but your own fiction, cherry picked from the 10,000 monkeys including the ones who take joy in feeding nonsense to the masses.

Go find Shakespeare. Don’t trust the monkeys. An if you’re one of the monkeys, my word, at least try to get something in with the filler.

Technology And Arts

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Sisyphean TechnologyPeople in technology of my era and later are strange creatures that delve into the depths of understanding the cold and relentless logic of systems that they create and maintain. We see the same in other fields, in Law, in Medicine, Accounting and so many others.

Today, as Lessig wrote, ‘Code is Law‘, and Law wrestles with technology even as technology works to circumvent existing Law. Law, as a freshman student will tell you, is not Ethics – it is an attempt at the codification of Ethics in a society. That distinction is important yet routinely forgotten by many – and that’s where some empowered by technology have an ax to grind. Others are just in it for the money, or for some political agenda.

One of the problems we face, as a global society of screen-watchers, is that we have separate silos of technology and arts – where technology is often used as a platform for the liberal arts.

The Limits of Open Data and Big Data

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Open Data Awards 2015A couple of days ago, one of the many political memes rolling around was how many police shootings there were under different presidencies. People were, of course, spewing rhetoric on the number of lethal shootings there were between one administration in the 1980s and one in the present. I’m being obtuse because this is not about politics.

The data presented showed that there were less shootings under one administration than another, but it was just a raw number. It had no basis in the number of police at the time, the number of arrests, or the number of police per capita.

I decided to dig into that.

The U.S. population has gone from roughly 227 million people (circa 1980) in that time to 318.9 million as of 2014. That’s fairly substantial. But how many police were there in the 1980s? A search on how many police officers there were in the 1980s was simply useless.

I went to the Bureau of Justice Statistics page on local police. It ends up that they only did any form of police officer census from 1992 to the present day in 4 year increments, which means that they didn’t have the data from the 1980s. If that’s true – if there was no data collected prior – it would mean that decisions were being made without basic data analysis back then, but it also means that we hit a limit of open data.

And I’d expended too much time on it (shouldn’t that be easy to find?), so I left it at that.

Assuming that the data simply does not exist, it means that the limit of the data is by simply not collecting it. I find it difficult to believe that this is the case, but I’ll assume good. So the open data is limited.

Assuming that the data exists but is simply not available, it means that the open data is limited.

The point here is that open data has limits, either defined by a simple lack of data or a lack of access to the data. It has limits by collection method (where bias can be inserted), by the level of participation, and so forth.

And as far as that meme, I have no opinion. “Insufficient data” – a phrase I’ve used more often than I should be comfortable with in this day and age.

Crisis Informatics

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DisasterPeople who have known me over the years know I’ve always had a passion for responding to disasters. I can’t tell you why it is that when most people are running away, I have a tendency to run in – something I did before I became a Navy Corpsman (and learned how to do better because of). Later became a stab on what this is about by first enabling the capture of the data itself by enabling the communication. I even worked a year at a company that does weather warnings and other emergency communication, and was disappointed at how little analysis was being done on the data.

Years later, I now read ‘The Data of Disasters‘. Some folks have been working on some of the things that I had been thinking about and working on as I had time, and they seem to have gotten further. I’m excited about since the Alert Retrieval Cache was necessarily closed and didn’t gain the traction I would have liked – and open systems present issues with:

  • Context: A post may be about something mentioned prior (a.k.a. ibid) but not tagged as such because of size limitations.
  • Legitimacy: Whether a source is trustworthy or not, and how many independent sources are reporting on something.
  • Timeliness: Rebuilding a timeline in a network full of shares/retweets can pose a problem because not everyone credits a source. If you go by brute force to find source date and times, you can pull on threads – but you’re not guaranteed of their legitimacy in unit time.
  • Perspectives: GIS allows for multiple perspectives on the same event in unit time.
  • Reactions: When possible, seeing when something at a site changes when all of the above can change in unit time.

It gets a bit more complicated from there – for example, languages can be difficult particularly with dialects and various mixes of languages (such as patois in the Caribbean, where I got into all of this). There’s also a LOT of data involved (big, quick and dirty data) that needs to be cleaned before any analysis can happen.

This is all why I envisioned it all to be a closed system, but the world believes differently, interjecting pictures of food with actual information of use. Like it or not, there’s data out there.

The expansion of data from a source over unit time, as mentioned in their paper on Crisis Informatics , is not something  I had thought of. I imagine they’re doing great work up there at the Department of Information Science in the College of Media, Communication and Information at CU Boulder.

I’ll be keeping an eye out on what else they publish. Might be fun to toss a beowulf cluster at some data.