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Ghosts, mechanical turks, and pseudo-AI (artificial intelligence)—Is it all a con game?

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There’s been more than one artificial intelligence (AI) story featured here on this blog but the ones featured in this posting are the first I’ve stumbled across that suggest the hype is even more exaggerated than even the most cynical might have thought. (BTW, the 2019 material is later as I have taken a chronological approach to this posting.)

It seems a lot of companies touting their AI algorithms and capabilities are relying on human beings to do the work, from a July 6, 2018 article by Olivia Solon for the Guardian (Note: A link has been removed),

It’s hard to build a service powered by artificial intelligence. So hard, in fact, that some startups have worked out it’s cheaper and easier to get humans to behave like robots than it is to get machines to behave like humans.

“Using a human to do the job lets you skip over a load of technical and business development challenges. It doesn’t scale, obviously, but it allows you to build something and skip the hard part early on,” said Gregory Koberger, CEO of ReadMe, who says he has come across a lot of “pseudo-AIs”.

“It’s essentially prototyping the AI with human beings,” he said.

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In 2017, the business expense management app Expensify admitted that it had been using humans to transcribe at least some of the receipts it claimed to process using its “smartscan technology”. Scans of the receipts were being posted to Amazon’s Mechanical Turk crowdsourced labour tool, where low-paid workers were reading and transcribing them.

“I wonder if Expensify SmartScan users know MTurk workers enter their receipts,” said Rochelle LaPlante, a “Turker” and advocate for gig economy workers on Twitter. “I’m looking at someone’s Uber receipt with their full name, pick-up and drop-off addresses.”

Even Facebook, which has invested heavily in AI, relied on humans for its virtual assistant for Messenger, M.

In some cases, humans are used to train the AI system and improve its accuracy. …

The Turk

Fooling people with machines that seem intelligent is not new according to a Sept. 10, 2018 article by Seth Stevenson for Slate.com (Note: Links have been removed),

It’s 1783, and Paris is gripped by the prospect of a chess match. One of the contestants is François-André Philidor, who is considered the greatest chess player in Paris, and possibly the world. Everyone is so excited because Philidor is about to go head-to-head with the other biggest sensation in the chess world at the time.

But his opponent isn’t a man. And it’s not a woman, either. It’s a machine.

This story may sound a lot like Garry Kasparov taking on Deep Blue, IBM’s chess-playing supercomputer. But that was only a couple of decades ago, and this chess match in Paris happened more than 200 years ago. It doesn’t seem like a robot that can play chess would even be possible in the 1780s. This machine playing against Philidor was making an incredible technological leap—playing chess, and not only that, but beating humans at chess.

In the end, it didn’t quite beat Philidor, but the chess master called it one of his toughest matches ever. It was so hard for Philidor to get a read on his opponent, which was a carved wooden figure—slightly larger than life—wearing elaborate garments and offering a cold, mean stare.

It seems like the minds of the era would have been completely blown by a robot that could nearly beat a human chess champion. Some people back then worried that it was black magic, but many folks took the development in stride. …

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Debates about the hottest topic in technology today—artificial intelligence—didn’t starts in the 1940s, with people like Alan Turing and the first computers. It turns out that the arguments about AI go back much further than you might imagine. The story of the 18th-century chess machine turns out to be one of those curious tales from history that can help us understand technology today, and where it might go tomorrow.

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[In future episodes our podcast, Secret History of the Future] we’re going to look at the first cyberattack, which happened in the 1830s, and find out how the Victorians invented virtual reality.

Philidor’s opponent was known as The Turk or Mechanical Turk and that ‘machine’ was in fact a masterful hoax as The Turk held a hidden compartment from which a human being directed his moves.

People pretending to be AI agents

It seems that today’s AI has something in common with the 18th century Mechanical Turk, there are often humans lurking in the background making things work. From a Sept. 4, 2018 article by Janelle Shane for Slate.com (Note: Links have been removed),

Every day, people are paid to pretend to be bots.

In a strange twist on “robots are coming for my job,” some tech companies that boast about their artificial intelligence have found that at small scales, humans are a cheaper, easier, and more competent alternative to building an A.I. that can do the task.

Sometimes there is no A.I. at all. The “A.I.” is a mockup powered entirely by humans, in a “fake it till you make it” approach used to gauge investor interest or customer behavior. Other times, a real A.I. is combined with human employees ready to step in if the bot shows signs of struggling. These approaches are called “pseudo-A.I.” or sometimes, more optimistically, “hybrid A.I.”

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Although some companies see the use of humans for “A.I.” tasks as a temporary bridge, others are embracing pseudo-A.I. as a customer service strategy that combines A.I. scalability with human competence. They’re advertising these as “hybrid A.I.” chatbots, and if they work as planned, you will never know if you were talking to a computer or a human. Every remote interaction could turn into a form of the Turing test. So how can you tell if you’re dealing with a bot pretending to be a human or a human pretending to be a bot?

One of the ways you can’t tell anymore is by looking for human imperfections like grammar mistakes or hesitations. In the past, chatbots had prewritten bits of dialogue that they could mix and match according to built-in rules. Bot speech was synonymous with precise formality. In early Turing tests, spelling mistakes were often a giveaway that the hidden speaker was a human. Today, however, many chatbots are powered by machine learning. Instead of using a programmer’s rules, these algorithms learn by example. And many training data sets come from services like Amazon’s Mechanical Turk, which lets programmers hire humans from around the world to generate examples of tasks like asking and answering questions. These data sets are usually full of casual speech, regionalisms, or other irregularities, so that’s what the algorithms learn. It’s not uncommon these days to get algorithmically generated image captions that read like text messages. And sometimes programmers deliberately add these things in, since most people don’t expect imperfections of an algorithm. In May, Google’s A.I. assistant made headlines for its ability to convincingly imitate the “ums” and “uhs” of a human speaker.

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Limited computing power is the main reason that bots are usually good at just one thing at a time. Whenever programmers try to train machine learning algorithms to handle additional tasks, they usually get algorithms that can do many tasks rather badly. In other words, today’s algorithms are artificial narrow intelligence, or A.N.I., rather than artificial general intelligence, or A.G.I. For now, and for many years in the future, any algorithm or chatbot that claims A.G.I-level performance—the ability to deal sensibly with a wide range of topics—is likely to have humans behind the curtain.

Another bot giveaway is a very poor memory. …

Bringing AI to life: ghosts

Sidney Fussell’s April 15, 2019 article for The Atlantic provides more detail about the human/AI interface as found in some Amazon products such as Alexa ( a voice-control system),

… Alexa-enabled speakers can and do interpret speech, but Amazon relies on human guidance to make Alexa, well, more human—to help the software understand different accents, recognize celebrity names, and respond to more complex commands. This is true of many artificial intelligence–enabled products. They’re prototypes. They can only approximate their promised functions while humans help with what Harvard researchers have called “the paradox of automation’s last mile.” Advancements in AI, the researchers write, create temporary jobs such as tagging images or annotating clips, even as the technology is meant to supplant human labor. In the case of the Echo, gig workers are paid to improve its voice-recognition software—but then, when it’s advanced enough, it will be used to replace the hostess in a hotel lobby.

A 2016 paper by researchers at Stanford University used a computer vision system to infer, with 88 percent accuracy, the political affiliation of 22 million people based on what car they drive and where they live. Traditional polling would require a full staff, a hefty budget, and months of work. The system completed the task in two weeks. But first, it had to know what a car was. The researchers paid workers through Amazon’s Mechanical Turk [emphasis mine] platform to manually tag thousands of images of cars, so the system would learn to differentiate between shapes, styles, and colors.

It may be a rude awakening for Amazon Echo owners, but AI systems require enormous amounts of categorized data, before, during, and after product launch. ..,

Isn’t interesting that Amazon also has a crowdsourcing marketplace for its own products. Calling it ‘Mechanical Turk’ after a famous 18th century hoax would suggest a dark sense of humour somewhere in the corporation. (You can find out more about the Amazon Mechanical Turk on this Amazon website and in its Wikipedia entry.0

Anthropologist, Mary L. Gray has coined the phrase ‘ghost work’ for the work that humans perform but for which AI gets the credit. Angela Chan’s May 13, 2019 article for The Verge features Gray as she promotes her latest book with Siddarth Suri ‘Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass’ (Note: A link has been removed),

“Ghost work” is anthropologist Mary L. Gray’s term for the invisible labor that powers our technology platforms. When Gray, a senior researcher at Microsoft Research, first arrived at the company, she learned that building artificial intelligence requires people to manage and clean up data to feed to the training algorithms. “I basically started asking the engineers and computer scientists around me, ‘Who are the people you pay to do this task work of labeling images and classification tasks and cleaning up databases?’” says Gray. Some people said they didn’t know. Others said they didn’t want to know and were concerned that if they looked too closely they might find unsavory working conditions.

So Gray decided to find out for herself. Who are the people, often invisible, who pick up the tasks necessary for these platforms to run? Why do they do this work, and why do they leave? What are their working conditions?

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The interview that follows is interesting although it doesn’t seem to me that the question about working conditions is answered in any great detail. However, there is this rather interesting policy suggestion,

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If companies want to happily use contract work because they need to constantly churn through new ideas and new aptitudes, the only way to make that a good thing for both sides of that enterprise is for people to be able to jump into that pool. And people do that when they have health care and other provisions. This is the business case for universal health care, for universal education as a public good. It’s going to benefit all enterprise.

I want to get across to people that, in a lot of ways, we’re describing work conditions. We’re not describing a particular type of work. We’re describing today’s conditions for project-based task-driven work. This can happen to everybody’s jobs, and I hate that that might be the motivation because we should have cared all along, as this has been happening to plenty of people. For me, the message of this book is: let’s make this not just manageable, but sustainable and enjoyable. Stop making our lives wrap around work, and start making work serve our lives.

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Puts a different spin on AI and work, doesn’t it?

Robots in Vancouver and in Canada (one of two)

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This piece just started growing. It started with robot ethics, moved on to sexbots and news of an upcoming Canadian robotics roadmap. Then, it became a two-part posting with the robotics strategy (roadmap) moving to part two along with robots and popular culture and a further  exploration of robot and AI ethics issues..

What is a robot?

There are lots of robots, some are macroscale and others are at the micro and nanoscales (see my Sept. 22, 2017 posting for the latest nanobot). Here’s a definition from the Robot Wikipedia entry that covers all the scales. (Note: Links have been removed),

A robot is a machine—especially one programmable by a computer— capable of carrying out a complex series of actions automatically.[2] Robots can be guided by an external control device or the control may be embedded within. Robots may be constructed to take on human form but most robots are machines designed to perform a task with no regard to how they look.

Robots can be autonomous or semi-autonomous and range from humanoids such as Honda’s Advanced Step in Innovative Mobility (ASIMO) and TOSY’s TOSY Ping Pong Playing Robot (TOPIO) to industrial robots, medical operating robots, patient assist robots, dog therapy robots, collectively programmed swarm robots, UAV drones such as General Atomics MQ-1 Predator, and even microscopic nano robots. [emphasis mine] By mimicking a lifelike appearance or automating movements, a robot may convey a sense of intelligence or thought of its own.

We may think we’ve invented robots but the idea has been around for a very long time (from the Robot Wikipedia entry; Note: Links have been removed),

Many ancient mythologies, and most modern religions include artificial people, such as the mechanical servants built by the Greek god Hephaestus[18] (Vulcan to the Romans), the clay golems of Jewish legend and clay giants of Norse legend, and Galatea, the mythical statue of Pygmalion that came to life. Since circa 400 BC, myths of Crete include Talos, a man of bronze who guarded the Cretan island of Europa from pirates.

In ancient Greece, the Greek engineer Ctesibius (c. 270 BC) “applied a knowledge of pneumatics and hydraulics to produce the first organ and water clocks with moving figures.”[19][20] In the 4th century BC, the Greek mathematician Archytas of Tarentum postulated a mechanical steam-operated bird he called “The Pigeon”. Hero of Alexandria (10–70 AD), a Greek mathematician and inventor, created numerous user-configurable automated devices, and described machines powered by air pressure, steam and water.[21]

The 11th century Lokapannatti tells of how the Buddha’s relics were protected by mechanical robots (bhuta vahana yanta), from the kingdom of Roma visaya (Rome); until they were disarmed by King Ashoka. [22] [23]

In ancient China, the 3rd century text of the Lie Zi describes an account of humanoid automata, involving a much earlier encounter between Chinese emperor King Mu of Zhou and a mechanical engineer known as Yan Shi, an ‘artificer’. Yan Shi proudly presented the king with a life-size, human-shaped figure of his mechanical ‘handiwork’ made of leather, wood, and artificial organs.[14] There are also accounts of flying automata in the Han Fei Zi and other texts, which attributes the 5th century BC Mohist philosopher Mozi and his contemporary Lu Ban with the invention of artificial wooden birds (ma yuan) that could successfully fly.[17] In 1066, the Chinese inventor Su Song built a water clock in the form of a tower which featured mechanical figurines which chimed the hours.

The beginning of automata is associated with the invention of early Su Song’s astronomical clock tower featured mechanical figurines that chimed the hours.[24][25][26] His mechanism had a programmable drum machine with pegs (cams) that bumped into little levers that operated percussion instruments. The drummer could be made to play different rhythms and different drum patterns by moving the pegs to different locations.[26]

In Renaissance Italy, Leonardo da Vinci (1452–1519) sketched plans for a humanoid robot around 1495. Da Vinci’s notebooks, rediscovered in the 1950s, contained detailed drawings of a mechanical knight now known as Leonardo’s robot, able to sit up, wave its arms and move its head and jaw.[28] The design was probably based on anatomical research recorded in his Vitruvian Man. It is not known whether he attempted to build it.

In Japan, complex animal and human automata were built between the 17th to 19th centuries, with many described in the 18th century Karakuri zui (Illustrated Machinery, 1796). One such automaton was the karakuri ningyō, a mechanized puppet.[29] Different variations of the karakuri existed: the Butai karakuri, which were used in theatre, the Zashiki karakuri, which were small and used in homes, and the Dashi karakuri which were used in religious festivals, where the puppets were used to perform reenactments of traditional myths and legends.

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The term robot was coined by a Czech writer (from the Robot Wikipedia entry; Note: Links have been removed)

‘Robot’ was first applied as a term for artificial automata in a 1920 play R.U.R. by the Czech writer, Karel Čapek. However, Josef Čapek was named by his brother Karel as the true inventor of the term robot.[6][7] The word ‘robot’ itself was not new, having been in Slavic language as robota (forced laborer), a term which classified those peasants obligated to compulsory service under the feudal system widespread in 19th century Europe (see: Robot Patent).[37][38] Čapek’s fictional story postulated the technological creation of artificial human bodies without souls, and the old theme of the feudal robota class eloquently fit the imagination of a new class of manufactured, artificial workers.

I’m particularly fascinated by how long humans have been imagining and creating robots.

Robot ethics in Vancouver

The Westender, has run what I believe is the first article by a local (Vancouver, Canada) mainstream media outlet on the topic of robots and ethics. Tessa Vikander’s Sept. 14, 2017 article highlights two local researchers, Ajung Moon and Mark Schmidt, and a local social media company’s (Hootsuite), analytics director, Nik Pai. Vikander opens her piece with an ethical dilemma (Note: Links have been removed),

Emma is 68, in poor health and an alcoholic who has been told by her doctor to stop drinking. She lives with a care robot, which helps her with household tasks.

Unable to fix herself a drink, she asks the robot to do it for her. What should the robot do? Would the answer be different if Emma owns the robot, or if she’s borrowing it from the hospital?

This is the type of hypothetical, ethical question that Ajung Moon, director of the Open Roboethics Initiative [ORI], is trying to answer.

According to an ORI study, half of respondents said ownership should make a difference, and half said it shouldn’t. With society so torn on the question, Moon is trying to figure out how engineers should be programming this type of robot.

A Vancouver resident, Moon is dedicating her life to helping those in the decision-chair make the right choice. The question of the care robot is but one ethical dilemma in the quickly advancing world of artificial intelligence.

At the most sensationalist end of the scale, one form of AI that’s recently made headlines is the sex robot, which has a human-like appearance. A report from the Foundation for Responsible Robotics says that intimacy with sex robots could lead to greater social isolation [emphasis mine] because they desensitize people to the empathy learned through human interaction and mutually consenting relationships.

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I’ll get back to the impact that robots might have on us in part two but first,

Sexbots, could they kill?

For more about sexbots in general, Alessandra Maldonado wrote an Aug. 10, 2017 article for salon.com about them (Note: A link has been removed),

Artificial intelligence has given people the ability to have conversations with machines like never before, such as speaking to Amazon’s personal assistant Alexa or asking Siri for directions on your iPhone. But now, one company has widened the scope of what it means to connect with a technological device and created a whole new breed of A.I. — specifically for sex-bots.

Abyss Creations has been in the business of making hyperrealistic dolls for 20 years, and by the end of 2017, they’ll unveil their newest product, an anatomically correct robotic sex toy. Matt McMullen, the company’s founder and CEO, explains the goal of sex robots is companionship, not only a physical partnership. “Imagine if you were completely lonely and you just wanted someone to talk to, and yes, someone to be intimate with,” he said in a video depicting the sculpting process of the dolls. “What is so wrong with that? It doesn’t hurt anybody.”

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Maldonado also embedded this video into her piece,

A friend of mine described it as creepy. Specifically we were discussing why someone would want to programme ‘insecurity’ as a  desirable trait in a sexbot.

Marc Beaulieu’s concept of a desirable trait in a sexbot is one that won’t kill him according to his Sept. 25, 2017 article on Canadian Broadcasting News (CBC) online (Note: Links have been removed),

Harmony has a charming Scottish lilt, albeit a bit staccato and canny. Her eyes dart around the room, her chin dips as her eyebrows raise in coquettish fashion. Her face manages expressions that are impressively lifelike. That face comes in 31 different shapes and 5 skin tones, with or without freckles and it sticks to her cyber-skull with magnets. Just peel it off and switch it out at will. In fact, you can choose Harmony’s eye colour, body shape (in great detail) and change her hair too. Harmony, of course, is a sex bot. A very advanced one. How advanced is she? Well, if you have $12,332 CAD to put towards a talkative new home appliance, REALBOTIX says you could be having a “conversation” and relations with her come January. Happy New Year.

Caveat emptor though: one novel bonus feature you might also get with Harmony is her ability to eventually murder you in your sleep. And not because she wants to.

Dr Nick Patterson, faculty of Science Engineering and Built Technology at Deakin University in Australia is lending his voice to a slew of others warning us to slow down and be cautious as we steadily approach Westworldian levels of human verisimilitude with AI tech. Surprisingly, Patterson didn’t regurgitate the narrative we recognize from the popular sci-fi (increasingly non-fi actually) trope of a dystopian society’s futile resistance to a robocalypse. He doesn’t think Harmony will want to kill you. He thinks she’ll be hacked by a code savvy ne’er-do-well who’ll want to snuff you out instead. …

Embedded in Beaulieu’s article is another video of the same sexbot profiled earlier. Her programmer seems to have learned a thing or two (he no longer inputs any traits as you’re watching),

I guess you could get one for Christmas this year if you’re willing to wait for an early 2018 delivery and aren’t worried about hackers turning your sexbot into a killer. While the killer aspect might seem farfetched, it turns out it’s not the only sexbot/hacker issue.

Sexbots as spies

This Oct. 5, 2017 story by Karl Bode for Techdirt points out that sex toys that are ‘smart’ can easily be hacked for any reason including some mischief (Note: Links have been removed),

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One “smart dildo” manufacturer was recently forced to shell out $3.75 million after it was caught collecting, err, “usage habits” of the company’s customers. According to the lawsuit, Standard Innovation’s We-Vibe vibrator collected sensitive data about customer usage, including “selected vibration settings,” the device’s battery life, and even the vibrator’s “temperature.” At no point did the company apparently think it was a good idea to clearly inform users of this data collection.

But security is also lacking elsewhere in the world of internet-connected sex toys. Alex Lomas of Pentest Partners recently took a look at the security in many internet-connected sex toys, and walked away arguably unimpressed. Using a Bluetooth “dongle” and antenna, Lomas drove around Berlin looking for openly accessible sex toys (he calls it “screwdriving,” in a riff off of wardriving). He subsequently found it’s relatively trivial to discover and hijack everything from vibrators to smart butt plugs — thanks to the way Bluetooth Low Energy (BLE) connectivity works:

“The only protection you have is that BLE devices will generally only pair with one device at a time, but range is limited and if the user walks out of range of their smartphone or the phone battery dies, the adult toy will become available for others to connect to without any authentication. I should say at this point that this is purely passive reconnaissance based on the BLE advertisements the device sends out – attempting to connect to the device and actually control it without consent is not something I or you should do. But now one could drive the Hush’s motor to full speed, and as long as the attacker remains connected over BLE and not the victim, there is no way they can stop the vibrations.”

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Does that make you think twice about a sexbot?

Robots and artificial intelligence

Getting back to the Vikander article (Sept. 14, 2017), Moon or Vikander or both seem to have conflated artificial intelligence with robots in this section of the article,

As for the building blocks that have thrust these questions [care robot quandary mentioned earlier] into the spotlight, Moon explains that AI in its basic form is when a machine uses data sets or an algorithm to make a decision.

“It’s essentially a piece of output that either affects your decision, or replaces a particular decision, or supports you in making a decision.” With AI, we are delegating decision-making skills or thinking to a machine, she says.

Although we’re not currently surrounded by walking, talking, independently thinking robots, the use of AI [emphasis mine] in our daily lives has become widespread.

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For Vikander, the conflation may have been due to concerns about maintaining her word count and for Moon, it may have been one of convenience or a consequence of how the jargon is evolving with ‘robot’ meaning a machine specifically or, sometimes, a machine with AI or AI only.

To be precise, not all robots have AI and not all AI is found in robots. It’s a distinction that may be more important for people developing robots and/or AI but it also seems to make a difference where funding is concerned. In a March 24, 2017 posting about the 2017 Canadian federal budget I noticed this,

… The Canadian Institute for Advanced Research will receive $93.7 million [emphasis mine] to “launch a Pan-Canadian Artificial Intelligence Strategy … (to) position Canada as a world-leading destination for companies seeking to invest in artificial intelligence and innovation.”

This brings me to a recent set of meetings held in Vancouver to devise a Canadian robotics roadmap, which suggests the robotics folks feel they need specific representation and funding.

See: part two for the rest.