Showing posts with label semibots. Show all posts
Showing posts with label semibots. Show all posts

Saturday, June 20, 2026

Pedagogy Meet Robogogy and Data as Labor


Seen above, a humanoid ponders its existence, instead of studying for its algebra exam. 

New theory explores how workers interact with technology in the modern workplace
Sep 2025, phys.org

This is about a new theory of workplace communication; the traditional version is called Social Exchange Theory, and it says we engage with people who are rewarding, and avoid people who are costly. Your co-worker might know a lot about a certain subject, but they talk your ear off.

The new theory is called Socio-Technical Exchange, and it says we develop "machine heuristics" - "When they felt expertise was important, people often preferred a human coworker, finding coworkers more efficient and knowledgeable. However, with simple or embarrassing questions, a machine was deemed a superior collaborator."

via University of Kansas: Cameron Piercy et al, Socio-Technical Exchange with Machines: Worker Experiences with Complex Work Technologies, Human-Machine Communication (2025). DOI: 10.30658/hmc.10.3

Image credit: hahahaha


Robots learn how to move by watching themselves
Feb 2025, phys.org

"Kinematic Self-Awareness"

"We humans are intuitively aware of our body; we can imagine ourselves in the future and visualize the consequences of our actions well before we perform those actions in reality. Ultimately, we would like to imbue robots with a similar ability to imagine themselves, because once you can imagine yourself in the future, there is no limit to what you can do."

via Creative Machines Lab at Columbia University School of Engineering and Applied Science: Yuhang Hu et al, Teaching robots to build simulations of themselves, Nature Machine Intelligence (2025). DOI: 10.1038/s42256-025-01006-w


Teaching AI models the broad strokes to sketch more like humans do
Jun 2025, phys.org

Their method, called "SketchAgent," uses a multimodal language model—AI systems that train on text and images to develop a "sketching language" in which a sketch is translated into a numbered sequence of strokes on a grid. The system was given an example of how things like a house would be drawn, with each stroke labeled according to what it represented — such as the seventh stroke being a rectangle labeled as a "front door" — to help the model generalize to new concepts.

via MIT CSAIL Computer Science and Artificial Intelligence Laboratory: Yael Vinker et al, SketchAgent: Language-Driven Sequential Sketch Generation, arXiv (2024). DOI: 10.48550/arxiv.2411.17673


Study argues online clicks and scrolls are 'thin labor' powering AI
Feb 2026, phys.org

Every time a user solves a reCAPTCHA or browses a social media feed, they provide the training data necessary for AI systems to function. Currently, tech giants extract this value without offering users any bargaining power or fair terms of engagement.

"We must decide if we are merely horses leaving digital manure behind or if we are the essential workers who build the intelligence of the future"

They advocate for the use of data unions, data strikes, and enhanced portability rights to give users a way to negotiate with massive platforms. By treating data as labor, the authors provide a framework for the public to exert collective power against the extractive practices of surveillance capitalism.

"Data strikes and data unions give the public a powerful tool to talk back to technology companies. When we act together to withhold or redirect our data, we transform from passive sources of information into a collective force that can reshape the digital economy to serve everyone, not just a few billionaires."

via Simon Fraser University and Carnegie Mellon University Tepper School of Business: Tae Wan Kim et al, Are We Horses? Rethinking Data as Labor, Philosophy & Technology (2026). DOI: 10.1007/s13347-026-01033-4

Like for example:
Meta to start capturing employee mouse movements, keystrokes for AI training data
Apr 2026, Reuters


Post Script of Martin Luther King Jr Quote About Greeley Meatpackers:
"As machines replace men, we must again question whether the depth of our social thinking matches the growth of technological creativity. We cannot create machines which revolutionize industry unless we simultaneously create ideas commensurate with social and economic reorganization, which harness the power of such machines for the benefit of man...the new age will not be an era of hope but of fear and emptiness unless we master this problem. Its solution will require forthright creative social planning from the shop level up to the highest levels of government."  
--Dr. King to the United Packinghouse Workers Union of America on May 21st 1962, and in response to Thousands of workers strike at one of the largest meatpacking plants in the US, Mar 16 2026, AP News [link

Friday, July 26, 2024

Never Go Full Robot


Evaluating truthfulness of fake news through online searches increases chances of believing misinformation
Dec 2023, phys.org

Searching to evaluate the truthfulness of false news articles actually increases the probability of believing misinformation.

Data voids are areas of the information ecosystem that are dominated by low quality information. They  be playing a consequential role in the online search process, sometimes leading to the appearance of non-credible information at the top of search results.

But we're not here for the results, we're here for the methods:

In order to study how people use the internet to search for the truthfulness of news, these scientists recruited their participants through Qualtrics and Amazon's Mechanical Turk, "tools frequently used in running behavioral science studies".

So let's make this point now, that these half-robot, semibot, half-automated services, which apparently support some of our behavioral science research, are getting closer to full-robot because the users (the workers, the mechanical turkers) are using AI to help them do their work, and so we may see some of our behavioral science research get lower in quality over time. And you thought there was a reproducability crisis in behavioral science before!

via NYU Center for Social Media and Politics and Stanford Law School: Kevin Aslett, Online searches to evaluate misinformation can increase its perceived veracity, Nature (2023). DOI: 10.1038/s41586-023-06883-y

Post Script:
Mechanical Turker is a word and you should probably know it.

Monday, July 15, 2024

Halving, Selving, and Other Words for Self Replication


A digital twin system that could enhance collaborative human-robot product assembly
Dec 2023, phys.org

The digital twin system creates a virtual replica of a scene in which a human and robot agent are collaborating, and plans effective collaborative strategies and executes them in a real-world environment; whereas previous systems relying on motion capture sensors struggle with occlusions, this one uses a human mesh recovery algorithm to reconstruct occluded human bodies.

via Nanjing University of Aeronautics and Astronautics in China: Zequn Zhang et al, Enabling collaborative assembly between humans and robots using a digital twin system, Robotics and Computer-Integrated Manufacturing (2023). DOI: 10.1016/j.rcim.2023.102691.

Partially related image credit: AI Art - AI Mark Zuckerberg Drinking Tea - 2024


First demonstration of predictive control of fusion plasma by digital twin
Jan 2024, phys.org

They're using a digital twin of a fusion reactor.

via Graduate School of Engineering at Kyoto University, National Institute for Fusion Science, of Natural Sciences, of Statistical Mathematics, and of Data Science Research, all in Japan: Yuya Morishita et al, First application of data assimilation-based control to fusion plasma, Scientific Reports (2024). DOI: 10.1038/s41598-023-49432-3


New 'digital twin' Earth technology could help predict water-based natural disasters before they strike
Mar 2024, phys.org

They developed digital twin case studies for the terrestrial water cycle in the Mediterranean Basin using new satellite data that measures soil moisture, precipitation, evaporation, river discharge, and snow depth as often as once a kilometer and once an hour.

via National Research Council of Italy: A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations, Frontiers in Science (2024). DOI: 10.3389/fsci.2023.1190191

Monday, September 19, 2022

Human Meat Restaurant


Unpaid social media moderators perform labor worth $3.4 million a year on Reddit alone
Jun 2022, phys.org

"2.8% of Reddit's 2019 revenue"

"Putting a price tag on the labor that people—in this case, content moderators on Reddit—have subsidized is leverage those moderators could wield when asking platforms for better resources and tools to help them monitor more effectively," Li said.

People, Space and Algorithms (PSA) Research Group at Northwestern. The group's overall mission is to "identify and address societal problems that are created or exacerbated by advances in computer science."

Li said a key part of the PSA Group's work involves re-framing user contributions to sites like Google, Facebook, Twitter and Reddit as "work"—not passive participation in online space—because companies use data and time that users provide to generate profit: to train their algorithms, better target advertising, recruit new users and ultimately earn more revenue.

This reframing led them to coin the term "data labor subsidy" when placing a dollar value on the contributions of tech platform users.

Not only do the users offer their data for free, but they also do the work of maintaining the platform for free; clever business model.

via People, Space and Algorithms Research Group at Northwestern: Hanlin Li, Brent Hecht, Stevie Chancellor, Measuring the Monetary Value of Online Volunteer Work. arXiv:2205.14528v1 [cs.HC], arxiv.org/abs/2205.14528

Also: Hanlin Li, Brent Hecht, Stevie Chancellor, All That's Happening behind the Scenes: Putting the Spotlight on Volunteer Moderator Labor in Reddit. arXiv:2205.14529v1 [cs.HC], arxiv.org/abs/2205.14529

Image credit: AI Art - Human Meat Restaurant, 2022
Prompt: human meat restaurant, horror, nightmare, cook, food, cooking. https://lexica.art/prompt/0a5b4f3f-f3e5-41b5-8942-d374325546e3


Human-like features in robot behavior: Response time variability can be perceived as human-like
Jul 2022, phys.org

Features of human behavior, namely response timing, can be translated into the robot in a way that humans cannot distinguish whether they are interacting with a person or a machine.

The human brain has sensitivity to extremely subtle behavior which manifests humanness," says Agnieszka Wykowska. "In our non-verbal Turing test, human participants had to judge whether they were interacting with a machine or a person, by considering only the timing of button presses during a joint action task."

The results showed that people interacting with the robot were not able to tell whether the robot was human-controlled or pre-programmed in the condition when the robot was in fact pre-programmed. This suggests that the robot passed this version of the non-verbal Turing test in this specific task.

via Italian Institute of Technology: F. Ciardo et al, Human-like behavioral variability blurs the distinction between a human and a machine in a nonverbal Turing test, Science Robotics (2022). DOI: 10.1126/scirobotics.abo1241.


How Facebook clickbait draws users into engaging with posts
Jul 2022, phys.org
  • The team collected 4,000 posts from seven consecutive days in late 2017 from ten U.S. and U.K. news outlets' Facebook pages, including "reputable" and "tabloid" sources. 
  • User engagement as measured by shares, comments and reactions
Results:
  • Unusual punctuation in the headline got 2.5 times more engagement.
  • Unusual punctuation in the text, however, got a decrease in engagement.
  • Questions in either the headline or the text did not get increased engagement.
  • Longer words in headlines got reduced engagement. 
  • The opposite was true for text.
  • Doubling the number of headline words led to 23.7% fewer comments, but no difference in reactions or shares.
  • The opposite for text, where all engagement increased with a doubling of the word count.
  • Common clickbait phrases in headlines — like "this will blow your mind" — were associated with a loss of around a quarter of engagement in comparison to those without such phrases.
  • In the sentiment analysis, negative wording in posts can increase comments
  • But for headlines, positive tone increases comments.
In other words, make sure your headlines have unusual punctuation and positive wording sentiment, and your text has longer words, more words, and negative wording sentiment.

And make sure your headlines DO NOT have questions, longer words, more words, or phrases "this will blow your mind", and that your text DOES NOT have unusual punctuation or questions.

via University of Duisburg-Essen: Click me…! The influence of clickbait on user engagement in social media and the role of digital nudging, PLoS ONE (2022). DOI: 10.1371/journal.pone.0266743

Tuesday, April 19, 2022

Characterization of Memetic Propagation via Digital Media and Algorithmic Amplification


AKA The Semibotic Socialization Machine

Ludwig Fleck already detailed much of this behavior in his 1935 book Genesis and Development of a Scientific Fact, a staggeringly prescient work when read in the zeitgeist of today. 

Controversy elicits engagement, and engagement facilitates polarization, since humans polarize themselves naturally. Or maybe it's the information polarizing itself, through us. Nonetheless, digital media enables algorithms to accelerate this natural dynamic. Now let's spread those two sentences over the next two pages:


Disagreement may be a way to make online content spread faster, further
Jul 2021, phys.org

Computational Simulation of Online Social Behavior (SocialSim) program of the U.S. Defense Advanced Research Projects Agency: exists

23,000 "controversial" posts about cybersecurity were seen by nearly twice the number of people and traveled nearly twice as fast when compared to 24,000 posts not labeled controversial (the Reddit definition of controversial is to have increasing numbers of both likes and dislikes). The controversial posts had 60,000 total comments, vs 25,000 for the non-controversial posts.

via University of Central Florida's Department of Computer Science: Jasser Jasser et al, Controversial information spreads faster and further than non-controversial information in Reddit, Journal of Computational Social Science (2021). DOI: 10.1007/s42001-021-00121-z

Here's a good example of what happens when we automate socialization with revenue prioritized over the public good:

"In a recent video, @jameslxke asks his followers why TikTok’s algorithm puts trans users in harm’s way by promoting their content on conservative For You pages. If the algorithm is smart enough to know each user’s identity and is intent on keeping users on its platform, @jameslxke reasons, then why does it put vulnerable users at risk for what he calls a “digital lynching”? In the comment section of @jameslxke’s video, users speculate that creating conflict serves the platform’s bottom line: “tiktok does it on purpose bc arguing/dialogue keeps people on the app & the shock value of sending videos to ppl who wont enjoy it boost their app.” By sharing experiences, asking questions, and crowdsourcing answers, teens are developing an algorithmic folklore while discerning the potential motivations behind TikTok’s software engineering.
-Strategic Knowledge: Teens use “algorithmic folklore” to crack TikTok’s black box, by Iretiolu Akinrinade for the Data & Society Institute on Jul, 2021 [link]


Viral true tweets spread just as far as viral untrue tweets
Nov 2021, phys.org

Correction -- in self-similar and metalogical form, the viral meme that fake viral memes spread farther and faster than the truth is actually not true. (If you're ever trying to make shit up that's crazier than what's really happening in the world, then you will fail.)

The problem is that we all know "a lie has spread halfway around the world before the truth has put its pants on". So when we hear that fake news is more fit, as in survival-of-the-fit, it makes perfect sense, and it sticks. Kind of like accidentally eating spiders in your sleep?

In this study, they looked at a part of network dynamics called "cascades", which follow the path a tweet takes as it spreads through the network. In this case, the cascade takes the form of retweets. It turns out that the cascade of true and fake tweets are indistinguishable. Now let's see how long it takes to correct this one. 

via Cornell University: Jonas L. Juul et al, Comparing information diffusion mechanisms by matching on cascade size, Proceedings of the National Academy of Sciences (2021). DOI: 10.1073/pnas.2100786118


People unknowingly group themselves together online, fueling political polarization across the US
Dec 2021, phys.org

They found that when people are less reactive to news, their online environment remains politically mixed. However, when users constantly react to and share articles of their preferred news sources, they are more likely to foster a politically isolated network, or what the researchers call "epistemic bubbles."

Once users are in these bubbles, they actually miss out on more news articles, including those from their preferred media outlets. Users seem to avoid what they deem as "unimportant" news at the expense of missing out on subjectively important news, the model shows.

Polarization of online social networks emerges naturally as people curate their feeds.

People who consume and share fake news might be inadvertently isolating themselves from everyone else who follows mainstream sources.
via Princeton: Polarized information ecosystems can reorganize social networks via information cascades, Proceedings of the National Academy of Sciences (2021). DOI: 10.1073/pnas.2102147118.


Why false news snowballs on social media
Dec 2021, phys.org

When a network is highly connected or the views of its members are sharply polarized, news that is likely to be false will spread more widely and travel deeper into the network than news with higher credibility. Even if people are rational in how they decide to share the news, this could still lead to the amplification of information with low credibility.

Important to understand the idea of "cost" in sharing information (and thus in the greater idea of memetic propagation) - "Nominal cost, for instance, taking some action, if you are scrolling on social media, you have to stop to do that. Think of that as a cost. Reputation cost might come if I share something that is embarrassing. Everyone has this cost, so the more extreme and the more interesting the news is, the more you want to share it." If the news affirms the agent's perspective and has persuasive power that outweighs the nominal cost, the agent will always share the news. But if an agent thinks the news item is something others may have already seen, the agent is disincentivized to share it.

Talking about information cascades, or news cascades, they say the credibility threshold is lower the more connected the network is and the more surprising the news is. But also, in a polarized network, where many of the nodes are likely to spread extreme views, the credibility threshold is also very low. 

"For any piece of news, there is a natural network speed limit, a range of connectivity, that facilitates good transmission of information where the size of the cascade is maximized by true news. But if you exceed that speed limit, you will get into situations where inaccurate news or news with low credibility has a larger cascade size," Jadbabaie says.

If the views of users in the network become more diverse, it is less likely that a poorly credible piece of news will spread more widely than the truth.

via Massachusetts Institute of Technology: Chin-Chia Hsu et al, Persuasion, News Sharing, and Cascades on Social Networks, SSRN Electronic Journal (2021). DOI: 10.2139/ssrn.3934010

Post Script:
Adaptive Metamemetics, Infectious Disease Networks, and Ludwig Fleck's Thought Collectives, 2020

Genesis and Development of a Scientific Fact. Ludwig Fleck, 1935 (Switzerland). Edited by Thaddeus J. Trenn and Robert K. Merton. Translated by Fred Bradley and Thaddeus J. Trenn. Foreword by Thomas S. Kuhn. Published by University of Chicago, 1979.

What Even Is 'Coordinated Inauthentic Behavior' on Platforms?
Wired Opinion. Sep 17, 2020. [soft paywall]

What Is ‘Coordinated Inauthentic Behavior’?
Snopes, Sep 4, 2021. [link]

Thursday, June 24, 2021

Now Hiring

AKA The Bot Market's Hot

ISIS still evading detection on Facebook report says
Jul 2020, phys.org

To amass digital territory is their purpose. It's been a while since I thought about the internet as real estate, or rather our eyeballs as real estate...
The Institute for Strategic Dialogue (ISD) tracked 288 Facebook accounts linked to a particular ISIS network over three months.

The researchers believe that at the centre of the network was one user who managed around a third (90 out of 288) of the Facebook profiles.

This was accomplished by generating real North American phone numbers and looking for associated Facebook accounts.

If it found a match it would request a re-set code to be sent to the phone number, so it could lock out the original account holder and use the Facebook profile to spread content.

The researchers say another key to the survival of ISIS content on the platform was the way in which ISIS supporters have learned to modify their content to evade controls. This included:
  • Breaking up text and using strange punctuation to evade any tools which would search for key words
  • Blurring ISIS branding, or adding Facebook's own video effects
  • Adding the branding of mainstream news outlets over the top of ISIS content
Image credit: Adeen Flinker NYU School of Medicine

Instagram removes hundreds of accounts tied to username hacking
Feb 2021, Reuters

But imagine that we're already semibots, and buying and selling each other.

Fake Amazon reviews 'being sold in bulk' online
Feb 2021, BBC News

It's the Amazon Marketplace, you can buy anything here:
The cost of fake reviews -  £5 each to start. These included "packages" of fake reviews available for sellers to buy for about £15 individually, as well as bulk packages starting at £620 for 50 reviews and going up to £8,000 for 1,000.
Researchers study online 'pseudo-reviews' that mock products
Apr 2021, phys.org

New fakes for the new world. Pseudo-fakes and quasi-forgeries. Pseudo reviews mock the product, like this example:
"I was able to purchase this amazing television with an FHA loan (30 year fixed-rate w/ 4.25% APR) and only 3.5% down. This is, hands down, the best decision I've ever made. And the box it came in is incredibly roomy too, which is a huge bonus, because I live in it now."
Apparently too many pseudo reviews can sway purchaser intent. And if a particular platform becomes infested with them, they can lose credibility altogether. 
via University of Akron: Federico de Gregorio et al. Pseudo-reviews: Conceptualization and consumer effects of a new online phenomenon, Computers in Human Behavior (2020). DOI: 10.1016/j.chb.2020.106545
Omegle: 'I'm being used as sex-baiting bot' on video chat site
Apr 2021, BBC News

God-level fake operation:

Kid goes to a website where you meet random strangers. An older woman convinces him to take off his clothes and go full Discovery Channel on himself. He does it again with other people. He quits the site, but then one day a year later, he goes back on and gets matched to ... himself. Someone uses his recorded video, overdubbed with typed conversations created in real time, in order to get other people to join. Who knows, maybe that's how he got convinced in the first place. 

"It was like a fully advanced system with different video sequences of me doing different stuff."

One day, the people running this "advanced system" won't be people or even a corporation, but an intelligent entity -- today we call it AI, but it will by then be a combination of people and computers all mashed together so you can't really tell who's who anymore. 

Army of fake fans boosts China’s messaging on Twitter
May 2021, AP News

This isn't really news, I added this one just for posterity.
Good term though: "Counterfeiting Consensus"

Mass scale manipulation of Twitter Trends discovered
June 2021, phys.org
"We found that 47% of local trends in Turkey and 20% of global trends are fake, created from scratch by bots. Between June 2015 and September 2019, we uncovered 108,000 bot accounts involved, the biggest bot dataset reported in a single paper. Our research is the first to uncover the manipulation of Twitter Trends at this scale," Elmas continued. (But don't forget to check how they define bot activity, as this can differ a lot.)
via  Ecole Polytechnique Federale de Lausanne: Ephemeral Astroturfing Attacks: The Case of Fake Twitter Trends. arXiv:1910.07783v4 [cs.CR] arxiv.org/abs/1910.07783
Conservatives more susceptible to believing falsehoods
Jun 2021, phys.org

Sorry guys:
Researchers found that liberals and conservatives in the United States both tended to believe claims that promoted their political views, but that this more often led conservatives to accept falsehoods while rejecting truths.

"But the deck is stacked against conservatives because there is so much more misinformation that supports conservative positions. As a result, conservatives are more often led astray."

Although the information environment was the primary reason conservatives were susceptible to misinformation, it may not be the only one.

Results showed that even when the information environment was taken into account, conservatives were slightly more likely to hold misperceptions than were liberals.

"It is difficult to say why that is," Garrett said. "We can't explain the finding with our data alone."

Conservatives also showed a stronger "truth bias," meaning that they were more likely to say that all the claims they were asked about were true.

"We show that the media environment is shaping people's ability to do this very basic, fundamental task."
via Ohio State University: R.K. Garrett el al., "Conservatives' susceptibility to political misperceptions," Science Advances (2021).

Post Script (Don't even try it)
The double-down is real: Correcting online falsehoods might make matters worse
May 2021, phys.org
Not only is misinformation increasing online, but attempting to correct it politely on Twitter can have negative consequences, leading to even less-accurate tweets and more toxicity from the people being corrected, according to a new study co-authored by a group of MIT scholars.
...
On Twitter, people seem to spend a relatively long time crafting primary tweets, and little time making decisions about retweets.
via Massachusetts Institute of Technology: Mohsen Mosleh et al, Perverse Downstream Consequences of Debunking: Being Corrected by Another User for Posting False Political News Increases Subsequent Sharing of Low Quality, Partisan, and Toxic Content in a Twitter Field Experiment, Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (2021). DOI: 10.1145/3411764.3445642
Post Post Script (Then again)
Artificial intelligence system could help counter the spread of disinformation
May 2021, phys.org

In total, they compiled 28 million Twitter posts from 1 million accounts, during the 2017 French elections, and found bots with 96% accuracy. Note that the way you define a bot is important in these studies. But also note that they've gone beyond using mere activity levels as their metric, they also look at how each bot causes the network as a whole to change and amplify messages, and at the bot's behaviors such as whether they interact with foreign media or what language they use.

Also, this approach looks at not just bots but the real people too, and how they all impact the network as a whole. 

via MIT Lincoln Laboratory's Artificial Intelligence Software Architectures and Algorithms Group: Steven T. Smith et al, Automatic detection of influential actors in disinformation networks, Proceedings of the National Academy of Sciences (2021). http://dx.doi.org/10.1073/pnas.2011216118DOI: 10.1073/pnas.2011216118

Friday, July 10, 2020

Sending Mixed Signals


Deep-learning system detects human presence by harvesting RF signals
Feb 2020, phys.org
The presence of humans in a room or in other indoor environments can alter the propagation of RF signals in several ways. By pre-processing RF channel measurements, the researchers were able to create 'images' summarizing the signals, which could in turn be analyzed to detect the presence of humans in a given environment. 
They then trained a CNN on a large amount of data containing both magnitude and phase information, two key properties of RF signals. Over time, the deep learning algorithm learned to distinguish when an environment is populated by humans and when it is free from them by analyzing what is known as channel state information (CSI). 
"Exploiting the ubiquity of ambient RF signals such as WiFi, Bluetooth or cellular signals for situational awareness information provides added value to existing RF infrastructure," Chen said. "Occupancy detection, for example, is an application where RF sensing can be a low-cost and infrastructure-free alternative or complement to existing approaches."

Saturday, September 14, 2019

On the Brains of Machines


This picture is kind of like an infrared camera but for algorithms.

It's a heat map for the eyeballs of a computer; what is it looking at, what are its clues?

In this case, it's looking at the water, not at the ship, in order to identify the image as a ship. (We're also assigning agency to this thing, in case anyone's keeping track.)

Neural nets are a big deal these days, but they come with a new problem. We don't know what they're doing, because the thing that makes them so special is that they figure out their own algorithm. (Agency again.) Computer programmers are not writing the programs; the networks write the programs using trial and error. Machine Learning is another name for this idea of iterative development.

There's a lot of people who would like to know what's going on in there, mostly to see how these things are getting their answers, and to make sure that the algorithms don't cheat to get their answers. Some learn bad habits, like detecting "ships" in pictures with water (which means they're good at detecting water, not ships), or by skimming metadata, which means they're good at classifying metadata, not pictures of stuff. These heat maps, and more importantly the forensics-like algorithms that inform them, are very helpful. They let us see inside the brains of the machine.

***
Speaking of disembodied brains, here's the artificial synapse. It uses a new type of hardware memory system that works more like a brain does, in an array, where they can do their computing business simultaneously. Neuromorphic computing.

And if you want to grow those artificial synapses in a 3-D tissue culture (brains in a dish), call these guys.

Cerebral organoids -- they're more for studying how the brain works than they are about making artificial brains. At least they're not using human brains, right?

Wrong; there are ethical concerns that these organoids might develop consciousness, or have already developed consciousness. 

Notes:

What is it like being a brain in a computer?
Clarifying how artificial intelligence systems make choices
Mar 2019, phys.org

Sebastian Lapuschkin et al, Unmasking Clever Hans predictors and assessing what machines really learn, Nature Communications (2019). DOI: 10.1038/s41467-019-08987-4

Fast, efficient and durable artificial synapse developed
Apr 2019, phys.org

Elliot J. Fuller et al. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing, Science (2019). DOI: 10.1126/science.aaw5581

Researchers grow active mini-brain-networks
Jun 2019, phys.org

Stem Cell Reports, Sakaguchi et al.: "Self-organized synchronous calcium transients in a cultured human neural network derived from cerebral organoids"
https://www.cell.com/stem-cell-reports/fulltext/S2213-6711(19)30197-3
DOI: 10.1016/j.stemcr.2019.05.029

On Free Will, Decision Making and Sovereign Awareness


Let's start here:
Our brains reveal our choices before we're even aware of them, study finds
Mar 2019, phys.org

Our thoughts can be predicted 11 seconds in advance by looking at patterns in brain activity.

"We believe that when we are faced with the choice between two or more options of what to think about, non-conscious traces of the thoughts are there already, a bit like unconscious hallucinations," Professor Pearson says.

"As the decision of what to think about is made, executive areas of the brain choose the thought-trace which is stronger. In, other words, if any pre-existing brain activity matches one of your choices, then your brain will be more likely to pick that option as it gets boosted by the pre-existing brain activity."
-Professor Joel Pearson, Director of the Future Minds Lab at UNSW School of Psychology

*note, researchers caution against assuming that all choices are by nature predetermined by pre-existing brain activity.
Roger Koenig-Robert et al. Decoding the contents and strength of imagery before volitional engagement, Scientific Reports (2019). DOI: 10.1038/s41598-019-39813-y

Aside from the idea of biases in general, This all reminds me of another article on digital telepathy:

A bunch of people each have a tetris game controller with only one button, so that one person's button rotates, the other slides sideways, etc. Together they have to make decisions by consensus, verbally, while they collaboratively control the tetris-block.

The division of labor is ruthless (only one button) but the communication is rich (human speech). The result is a complex procedure that has been stripped-down to operate in a digitally-mediated environment.

Then there's the straight telepathy style collaboration where they bypass the verbal communication and go straight to brain waves:
How you and your friends can play a video game together using only your minds
July 2019, University of Washington News

A University of Washington team is doing telepathinc collective problem-solving. It's called BrainNet. Three people play a Tetris by talking to each other with their brain waves and wireless signal.
As in Tetris, the game shows a block at the top of the screen and a line that needs to be completed at the bottom. Two people, the Senders, can see both the block and the line but can’t control the game. The third person, the Receiver, can see only the block but can tell the game whether to rotate the block to successfully complete the line.

Each Sender decides whether the block needs to be rotated and then --passes that information from their brain, through the internet and to the brain of the Receiver.-- Then the Receiver processes that information and sends a command — to rotate or not rotate the block — to the game directly from their brain, hopefully completing and clearing the line.  
The screen also showed the word “Yes” on one side and the word “No” on the other side. Beneath the “Yes” option, an LED flashed 17 times per second. Beneath the “No” option, an LED flashed 15 times a second. Once the Sender makes a decision about whether to rotate the block, they send ‘Yes’ or ‘No’ to the Receiver’s brain by concentrating on the corresponding light [which then sends frequency-specific signal downstream].
-University of Washington
If we take this splintered form of decision-making, and combine it with the fact that we don't seem to be making decisions in the way that we think we are (the decision is already made seconds before we realize it), then it would be expected that as we get better at collaborating and complexifying our distributed cognition network, we will have robots, i.e., artificially intelligent entities, helping us, and becoming part of us.

Scale this up and imagine 700 people collectively coordinating a robot's movements, but not just one robot, hundreds and thousands. All semibots, no more line between us.



Notes:
We have come a long way since Emotiv's EPOC headset almost a decade ago; just imagine 2030.

Try Not to Think
Network Address, 2017

All Your Brain Are Belong To Us
Network Address, 2012

Playing Tetris by committee
May 2019, BBC

^Developed by Patrick Lemieux of UC Davis, California, the Octopad single button controllers mean each player can only trigger one kind of movement in the game so it forces co-operation and conversation between players.

Post Script:
Shared control allows a robot to use two hands working together to complete tasks
May 2019, phys.org
A team of researchers from the University of Wisconsin and the Naval Research Laboratory has designed and built a robotic system that allows for bimanual robot manipulation through shared control.... a technique that enabled a robot to carry out bimanual tasks by sharing control with a human being. ... The robot did not progress to the point of performing the task on its own—instead, it learned to serve as a more fully capable augmented assistant.
Pedestrians at crosswalks found to follow the Levy walk process
Apr 2019, phys.org

As people cross an intersection, they interface each other in predictable ways. 

"Rather than people continually meeting face to face, walkers would simply follow a person moving in the same direction, preventing the constant need to shift their path. ... Doing so increased efficiency both for the individuals and for the crowd as a whole."

They also found that these streams followed a Lévy process.

...
The Lévy walk process is a mathematical description, which means it's predictable. It says that as you walk, or as your eyes dart across a screen, or as you do a whole bunch of repetitive actions, you will move in short stops interspersed with long stops. Many short strides intermittent with some long strides. But the ratio of short to long, and the distances of each, are determined by a power law distribution that is the Lévy process. That our walking follows a Lévy process means we can predict how many steps you will take as you cross a given intersection.

And if you happen to be walking funny because you have a shotgun in your trousers, that can now be recognized by a persistent surveillance system, to either alert in advance of atypical behavior, or to aid in identifying individuals of interest in footage of an event after it has taken place. 

Wednesday, January 23, 2019

Fauxbots



Robots are already taking over.

Human computer programmers are influencing memetic propagation algorithms which are influencing human social media users. Another way of articulating this is to say that we are outfitting ourselves with a cybernetic limbic system. I'm channeling both Elon Musk's far-out interview about artificial emotional intelligence ecologies and Jaron Lanier's recent behavior modification talks (with a bit of Robert Sapolsky's Human Behavior lectures).

As if it wasn't a surprise, news has it that a script designed to spread information is better than us at doing just that. Coupled with the fact that misinformation spreads faster than factual information, we can easily see what a bad idea it was to offload water-cooler-style information-spreading to an algorithm optimized to sell consumer goods and services to a hypertargeted audience.

This is not to talk trash about technology, or social media, or even human nature; there's plenty of good things to come of all this. I mean, ALS, right?

It is an alert, however, that the things that we fear from far away (robot overlords etc), they tend to look a lot different by the time they get right under our nose. And this is a great example. Note that researcher Tim Hwang was doing work with SocialBots back in 2012, when he ran a competition to see who could influence the most people on Twitter with an automated fauxbot. By the end of the competition we learned two things - 1.It's not hard at all to make people think you're a person when you're not, and 2.It's very very ethically questionable to do these kinds of experiments.

Not that it matters much. Using a social media platform waives your right to be free from experimentation.

In what I guess I will call traditional research, if your experiment involves people, you have to take some ethics classes, and your plan has to pass a group of people who's job it is to make sure you're not doing anything ethically dubious to your subjects. In very simple terms, you're not supposed to do harm to your subjects (only people though, sorry animals).

But when you participate in social media, you're willfully participating in the experiment that is the platform's digital ecosystem (and because the programs aren't programming themselves, not yet, the platform's corporate culture has influence here as well). The whole thing is an experiment from the moment you log in.

So what happens when you are that poor schmuck who fell in love with Tim Hwang's socialbot and then got his heart broken when the competition ended? Tough shit?

Or when you realize the "woman" you've been chatting up for the past two days is really a feature designed by the dating app itself to keep you engaged at the most opportune moments; what is a melted snowflake to do? Who to sue?

Listening to the news last night, two people are talking about results from a recent Facebook experiment that showed we can make people act nicer to each other through pretty simple and very subtle programming changes. Or make people happier by showing them happier news in their feed. (It's called a feed for f's sake.)

Is a social media platform responsible for the death of a teen who may have been only a few happy newsclips away from making that final decision?

Nope. Not right now at least. Not until we face the hard facts about how powerful it is to effect mass population manipulation with only minor changes in program code.


Post Script:
The chances you've been involved in one of these experiments already? 100%

"Low-credibility content" is the new fake news, and "auto amplification" is the act of spreading it.

The reason automated amplification works is because of herd mentality. A great experiment I read recently in Geoffrey West's book Scale - a researcher took 100 crowdfunding campaigns that had been at $0 for a minute already and donated $1 to half of them. The ones who got no donation stayed at zero, and the others gained at least some extra donations. There are dozens of other names for this such as the law of accumulative advantage, the Matthew Effect, and the rich get richer.


Notes:
Study: It only takes a few seconds for bots to spread misinformation
Nov 2018, Ars Technica

The spread of low-credibility content by social bots
Nature, 2018

The spread of true and false news online
Science, 2018

The spread of true and false information online
MIT, 2018

I'm Not a Real Friend, But I Play One on the Internet
Tim Hwang, HOPE#9, July 2012

SocialBots
Network Address, 2012

Institutional Review Board
also known as an independent ethics committee, ethical review board, or research ethics board, is a type of committee that applies research ethics by reviewing the methods proposed for research to ensure that they are ethical

Post Post Script Script:
Looks like something is real popular in the news right now:

On Twitter, limited number of characters spreading fake info
Jan 2019, phys.org

Washington fears new threat from 'deepfake' videos
Jan 2019, The Hill


Monday, June 4, 2018

The True Limits of Believability



Not a bad problem to have. Robot voices have become so good that we can't tell they're robots anymore. But this is against our unspoken code of ethics; we as humans have to know when we're dealing with something that is indistinguishable from a human when it's not. (Unless it's a dating website of course.)

Notes

What happens when the robots sound too much like humans?
May 2018, phys.org

The assistant added pauses, "ums" and "mmm-hmms" to its speech in order to sound more human as it spoke with real employees at a hair salon and a restaurant.

Monday, September 25, 2017

Bots Made Me Do It


Twitter bots for good: Study reveals how information spreads on social media
Sep 2017, phys.org

Players:
Emilio Ferrara, a USC Information Sciences Institute computer scientist and research assistant professor at the USC Viterbi School of Engineering's Department of Computer Science, and a team from the Technical University of Denmark.

Experiment:
39 bots deploy "positive-themed" hashtags to 25,000 Twitter users for four-months.

Conclusion:
Information is much more likely to become viral when people are exposed to the same piece of information multiple times through multiple sources. "This milestone shatters a long-held belief that ideas spread like an infectious disease, or contagion, with each exposure resulting in the same probability of infection," says Ferrara. -phys.org
https://phys.org/news/2017-09-twitter-bots-good-reveals-social.html

Source:
Bjarke Mønsted et al. Evidence of complex contagion of information in social media: An experiment using Twitter bots, PLOS ONE (2017). DOI: 10.1371/journal.pone.0184148

image source
image credit

Post Script:

Post from 5 years ago about this topic, check out Tim Hwang at the HOPE#9 conference talking about his ethically and legally dubious twitter-bot experiments on an unsuspecting cluster of 500 users:
Social Bots, Network Address, 2012

In case you were wondering the difference between robo- and -bot
Robo vs Bot, Network Address, 2013

Aaaaaand, why are we still not using the word "semibots?"
The Semibots Are Coming, Network Address, 2015


Saturday, May 20, 2017

Semibotic Semibiotic


It's not often you get to see an article about consciousness on the BBC, but you do, it's Dan Dennett getting mega-memetical. (just kidding, that doesn't even make sense, in this context.)

Is consciousness just an illusion?
Apr 2017, BBC

We're not just are robots", he says. "We're robots, made of robots, made of robots".
-Dan Dennett

Thursday, November 24, 2016

Wetbots


Patterns are everywhere, and now recognition is more popular than it's ever been. The performance of pattern recognition has been relegated to the domain of the living, the wetware among us. But advances in biocomputing, organic computing, neural-interfaced prosthetics, semibots, synthetic life, artificially intelligent unsupervised learning entitites, etc. have blurred the line of what we consider to be alive, and can be intelligent. Squishy robots they're called here --

From University of Pittsburgh's Swanson School of Engineering, via phys.org:

Dr. Yashin said that patients recovering from a hand injury could wear a glove that monitors movement, and can inform doctors whether the hand is healing properly or if the patient has improved mobility.

Another use would be to monitor individuals at risk for early onset Alzheimer's, by wearing footwear that would analyze gait and compare results against normal movements, or a garment that monitors cardiovascular activity for people at risk of heart disease or stroke.

Research into 'materials that compute' advances as engineers demonstrate system performs pattern recognition
phys.org, Sep 2016
http://phys.org/news/2016-09-materials-advances-pattern-recognition.html

Sunday, December 20, 2015

The Semibots Are Coming


astronaut painting by Jeremy Geddes 


Talk about artificial intelligence becoming sentient needs to be tempered by the grey-area of semi-autonomy, or the half-robot half-human, because that's where it's really at.

Some fembots are all-robot, but the ones that will really getcha are the ones that are real people working along with intelligent algorithms, and I like to call these semibots.

How Ashley Madison Hid Its Fembot Con From Users and Investigators
Gizmodo, Sep 215

Ashley Madison created tens of thousands of fembots to lure men into paying for credits on the “have an affair” site. When men signed up for a free account, they would immediately be shown profiles of what internal documents call “Angels,” or fake women whose details and photos had been batch-generated using specially designed software. To bring the fake women to life, the company’s developers also created software bots to animate these Angels, sending email and chat messages on their behalf.

To the Ashley Madison “guest,” or non-paying member, it would appear that he was being personally contacted by eager women. But if he wanted to read or respond to them, he would have to shell out for a package of Ashley Madison credits, which range in price from $60 to $290. Each subsequent message and chat cost the man credits. As documents from company e-mails now reveal, 80 percent of first purchases on Ashley Madison were a result of a man trying to contact a bot, or reading a message from one. The overwhelming majority of men on Ashley Madison were paying to chat with Angels like Sensuous Kitten, whose minds were made of software and whose promises were nothing more than hastily written outputs from algorithms.