Month: March 2019

A recent Technology Review article citing trends in AI research caught my eye. While we like to say there’s nothing new under the sun, AI research should be literally new–or is it?

The three most common paradigms in the pursuit of true AI are knowledge-based systems, machine learning, and more recently reinforcement learning.

But these aren’t new approaches at all. Many have been around since the 1950s. But as processing speeds increase and neural networking comes into its own, they are all vying for the limelight.

Knowledge based systems were very popular initially because they boiled the knowable world down into rules. If there’s a thought, there’s a rule for it, the logic went. So researchers built more and more rules until the systems were such a glut of rules that they couldn’t get out of their own way.

Supervised learning, using neural networks, got a big boost in 2012 when Geoffrey Hinton and his team from the University of Toronto beat everyone at ImageNet by more than ten percentage points–moving the needle not incrementally, but massively. But deep learning requires so much labeled data that it can take weeks and require petabytes of data to build a knowledge set with discriminative capabilities. This is what we generally think of as Machine Learning.

The new, old, kid on the block, Reinforcement Learning, has seen a huge increase in research paper mentions. Reinforcement “mimics the process of training animals through punishments and rewards.” Reinforcement languished for many years until 2015 when DeepMind’s AlphaGo beat the Go world champion.

So whether its Reinforcement Learning, Knowledge Based systems or Bayesian networks, no one knows. In the article Pedro Domingos of the University of Washington and author of The Master Algorithm says either another older paradigm will rise to the surface again or we could see something entirely new.

I am one of those blithe technologists who doesn’t really care that Google knows where I am, what I’m interested in, and who I know. But I also know that I don’t like Facebook for exactly the same reasons. As I am a pastiche of the choices I make, I accept some cognitive dissonance related to something like data.

And if you insist on either total privacy or data freedom, then I would ask you if you only eat foods that are healthy for you or bad for you? Do you exercise every day or when you can, or just when you feel like it? Do you never speed when driving, or do you speed sometimes?

Just as with life choices, we make decisions about our data the same way. This is both good and bad. When a birth date is demanded of me by some website, I often lie. Their data is now corrupt, but usually within a few days of my actual birth date, so for their purposes perhaps close enough is good enough.

Ideally, our data would flow anonymously to all the corporations and governments that need to make use of it. Right now, of course, the US Government doesn’t collect a lot of data that could protect us, and does collect some stuff that constitutes an invasion of privacy.

Of course Big Data can (and will) be used for troubling purposes. But it could also rectify current injustices caused by ‘broad brush’ data mining. If you have perfect credit but live in a neighborhood and have an income that would generally suggest you aren’t credit-worthy, broad brush data might suggest you not receive a mortgage to buy a house.

In other words, I don’t believe we need to know all the ramifications of varying levels of privacy or lack thereof before moving forward into a new, autonomous age. Humans are really good at solving problems. They also create a lot of them on the way.

I recently came across a new podcast over at QZ, addressing the issue of whether all technology is good all the time, called Should This Exist?

Questions about neurohacking, CRISPR babies, empathetic robots, etc. abound, but it’s obvious, a lot of tech is not good at all.

Neurohacking, where you either use drugs or electricity to stimulate the laying down of memory pathways in the brain might be great, right? But since we just barely learned how the brain works, and not even that, entirely, I’d rather stick to practicing my skills and using something like Neuro Linguistic Programming (NLP – confusingly the same acronym as Natural Language Processing) to get me there. And it was scientists who told us that SSRIs would solve all our emotional problems, not understanding that removing the SSRIs would result in neurochemical imbalances in the brain for, possibly, the rest of the user’s life.

CRISPR could be great at saving lives and eliminating genetic disease, but could also be used for what racist scientists in the 19th and 20th centuries called Eugenics. I don’t know if humans are yet wise enough to wield such powerful technology.

And of course, Big Data looms over all. A lot of people don’t want their data out there. A lot of people believe that our data will be misused by corporations, governments and law enforcement. Benjamin Franklin said, “Those who would give up essential Liberty, to purchase a little temporary Safety, deserve neither Liberty nor Safety.”

I don’t know what Liberty means today, and I’m not sure what Safety is, either. Is Liberty being able to do things without anyone’s knowledge? Or is Liberty being free do what we want. I’m a big fan of Benjamin Franklin, but I’m an even bigger fan of Franklin Delano Roosevelt. His Four Freedoms speech defined what we, as society, should be aiming for for all our citizens.

And if we’re looking for universal Freedom of Speech, Freedom of Worship, Freedom from Want and Freedom from Fear, technology supports those things. Technology has enabled so much Free Speech right now that it’s actually a burden to call out idiots on their racism and ignorance. Even if you live in deepest, darkest Mississippi, you can choose your faith, and you can be an active online member of any religious community. We haven’t reached Freedom from Want, but technology, as always, could get us there–the main block to advances on the Want front come from greedy, frightened humans. Lastly, how do we free ourselves from Fear? Education and knowledge are the only medicines for that, and technology is bringing (along with all that mucky free speech) more information to more people than ever before.

And it can be scary that the G-MAFIA tracks almost all our public data. But when one of them went rogue, selling our private data to Russians (Facebook), a lot of people called them out. Were they pilloried? Pretty much, yes. But they weren’t forced out of business. We like their business, and the Russians and Cambridge Analytica paid them to buy our publicly shared information. I don’t know, but if you’re shocked by a business selling what you give them for free, you really need to bone up on your privacy practices.

In the end, things that exist exist, and those pesky, curious humans will not stop inventing new, ever more dangerous tools. You can’t put the genie back in the bottle. Far better to try to process our anxieties and agree through the social contract what appropriate protocols should be put in place.

Some really exciting stuff is happening in the natural language processing (NLP) field. If you didn’t already know about it, Google Duplex, the successor, or upgrade to Google Assistant, has already rolled out in key markets (if you don’t live in NYC or San Francisco you probably don’t have access).

OpenAI researchers have created a process by which AI “learns” from unlabeled text. This is essentially the process of letting the AI teach itself language by picking it up on the fly, the way humans learn it. This is a major step toward real AI conversations, where the AI isn’t just interpreting keywords related to a set menu.

Another mind expanding program at Google is developing a structure for AIs to fill in words it can’t hear.

Once these roll out, your Google Assistant will become an RPA all its own. This will revolutionize your personal life. Why not find out how RPAs can help your business in the same way? Check out real-life interactions between Google Duplex and humans here.