A new SafeSearch for the epoch of hate

In the bad old days, just before yesterday, the main thing wrong with the Internet/Interweb was that it was awash with porn. Thankfully, browser providers such as Microsoft and Google came up with SafeSearch, which allowed you to automatically filter out this torrent of filth.

Today the Interweb is awash with people trying to convince you of fake news. Sometimes they distort information or just plain lie to you, sometimes they express discomfiting opinions which they ought to have self-censored .. and sometimes they expose you to true information about the world which is deeply upsetting or brand-damaging.

Google/YouTube has been slow to pull down (somewhat-popular) offending content. I was shocked, shocked to realise that there was a conflict of interest here. Luckily the big advertisers are on the case. In The Times today I read: "JP Morgan’s firewall blocks ads from YouTube hate videos".

Yes, hate. So bad for the brand.

"Google has been accused of failing to do enough to remove dangerous content from YouTube after a leading bank created its own tools to prevent its online advertisements appearing alongside hate-filled videos.

Politicians and advertisers said it was an indictment of Google that a financial company was able in effect to identify and filter racist and terrorist clips where the tech giant had failed.

JP Morgan Chase devised an algorithm with 17 layers, or filters, to separate what it deems as safe YouTube channels from unsafe ones. One of the filters assesses the total video count on a channel, which automatically cuts out channels with one-off viral videos. Other filters look at channels’ subscriber counts, the topics they focus on, the language of the video captions and viewer comments on their clips.

“The model Google has built to monetise YouTube may work for it, but it doesn’t work for us,” Aaron Smolick, executive director of paid-media analytics and optimisation at JP Morgan Chase, told Business Insider. “The attention of protecting a brand has to fall on the people within the brand.”

Do we even want Google or Facebook to be the arbitrators of what can be published on the Interweb? Times commentator David Aaronovitch is not so sure:

"We all accept that material inciting terrorism or showing child sexual abuse should be removed immediately. But what happens when companies are obliged to take down anything that constitutes hate speech or intimidation?

Leaving aside the question of how you define them, the approach would almost certainly involve creating algorithms that delete material with certain keywords or phrases as soon as they are posted.

For one thing, this would save tech giants the trouble of having to respond to potentially millions of requests to take down material that users found offensive.

Better to make the mistake of wrongful deletion of posts and accounts, for which there is no penalty, than to allow something bad to get through and get dragged through the courts."

The world according to Google. I'm sure Hillary Clinton and George Osborne would approve.

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There is a better way.

Extend the concept of SafeSearch the JP Morgan way. Consider a firewall-like app which can download 'safe-to-view' rules. Anyone can design a rule set: the US Democratic Party, SJWs-against-hate, Fox News, The Sun newspaper, .. JP Morgan .. .

Any organisation which fears brand damage will simply white-list those rule-sets from organisations which filter content in an acceptable manner. The app will then block their ads in proximity to texts, pictures and videos deemed to be those of hate. The ads will only be served to those devices running the app with a white-listed rule-set; I think JP Morgan et al could swing that.

This decentralised solution removes our reliance on those compromised Silicon Valley giants. We can all live safely in our bubble of choice.

Seriously, what is there not to like?

Time to go post-Google

For a long time I used to not care about Internet privacy. And then Google got into SJW mode and ceased to be my friend. I read about its business model, the Amazonian torrents of cash that advertisers pour into its coffers .. and I wondered if it would always have my best interests at heart.

So I decided to use DuckDuckGo for all those searches which I'd like to keep from the planetary AI. But Google, and my ISP, still know way too much.

... but you're never alone with a keylogger

On my Android devices, the DuckDuckGo app has a setting to 'enable Tor' which I checked. It then helpfully prompts you to install the Tor router Orbot and the Tor browser Orfox. It's easy.

Orbot does not provide generic anonymous Internet access; programs have to be configured to work with it. Basically things work best if you access websites via the Tor Browser .. which is the search term for Windows PCs.

The thing is, I know that the AI assistant we're slowly crawling towards will only work if it knows more about you than your closest confidante. And it will live in the Cloud. But I would pay to have that knowledge base under my control and lodged with a trusted third party (like the folks running ProtonMail).

Keyloggers

Google's middleman offer to advertisers and you & me is based on the twin peaks of narrow domain expertise, increasingly based on neural net AI such as Google Translate and voice recognition, and its ability to integrate across its apps which thread to so much of our lives: email, photos, calendar, notes, search queries, etc.

Google does the bulk of this information centralisation and synthesis in the Cloud: that is, on its own servers. The resulting real-time data model of you both repopulates your apps (Chrome talks to Gmail talks to Calendar talks to Google Now talks to GPS talks to Maps ...) and is sold to advertisers for targeting.

If we're to bring that level of integration back into our own hands, then we need to capture our activity across many different apps and device functions. Perhaps one day all apps will have a standard API with which to talk to our personal assistant app .. but until then it's a benign keylogger I'm afraid.

The other people who are big fans of keyloggers are the intelligence services and those vendors (like Microsoft) who are losing out in the race for ubiquitous ownership of our most popular apps.

Replika is massively oversold

Replika was originally going to be your own, online personal doppelgänger. Given the current state of the art with chatbots (tiresome and useless), that was always going to be a stretch.

The current PR says:

"Replika is your personal AI friend that you nurture and raise through text conversations. It is a lifetime companion who is always there for you, chats with you, keeps your memories, and helps you become more connected to yourself."

They're busy trying to create doable spin-offs such as a personal diary ("A Cute Diary That Keeps Itself").

Given date-slippage, I had thought that the whole Replika thing might have silently collapsed, but I suppose there is no shortage of people who are happy to update a super-Eliza forty times a day with details of their every mundane activity.

Facebook.

There would be a lot of interest in a virtual friend, endlessly attentive and caring  (except that's not a friend, more a courtier - artificial sycophancy). But if this were in the state of the art, one of Google, Microsoft, Facebook, Amazon or Baidu would have done it already. It's plainly on the future roadmap for the plethora of voice assistants, but today's systems are no more than super-recognisers.

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Have you ever had the experience of being in a technical meeting, in an area not wholly in your sphere of competence, and suddenly you lose the plot? For a moment, you just don't know what everyone else is talking about. You pray no-one will ask for your opinion.

If you're lucky, in a minute or two the topic will move on and you will rejoin the shared context.

What happened there? The participants shared an internal cognitive model of what the conversation was about, and yours frayed. But no chatbot today can maintain an internal model of any complexity.

Worse: the topics of mundane discourse are open-ended, rooted in a complex culture and often private. Do we even want our AI-in-the-cloud to share personal and family intimacies, possibly with any interested intelligence agency?

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Your Replika AI friend is going to get 40 bland texts per day from you. Some of the questions already seem rather intrusive.

There is a hint of blank-slate about current AI. As if one standard optimised neural-net architecture could create the ideal artificial personality template, which then gets loaded with data to become an individual.

We know that people aren't like that. Common experience and psychometric data tells us that people have distinct personalities, that these are strongly heritable and resistant to change. We all know, as folk psychologists, that we deal with people as distinct individuals, not clones. And that most of those differences are innate and resistant to social influences.

"She thinks she can change him!"

No she can't.

So many mountains to climb.

• Why is the brain structured as modules, not one uniform design?
• How is the architecture of personality differences implemented?
• How to immerse an AI in common knowledge, culture and mores?
• How does social deftness, tact and propriety work?
• What's an effective, useful and pleasant engagement model - corporeal?

Yes, I am prepared to be disappointed with Replika.

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Update: 9th March 2017.

"Replika AI to launch on the App Store

"Today, we are excited to announce that Replika will appear on the Apple’s App Store on March 13 at 12:00 AM Pacific time. We’d like to thank all the participants of the app’s preview in Testflight for the incredible feedback that helped us shape the app."

Perhaps no-one understands Maxwell's equations

"Microsoft CEO Satya Nadella spoke at a public event in India on Monday ...

"The first time I put on a HoloLens was to see something Cleveland Clinic [a non-profit academic medical center] had built for medical innovation... As an electrical engineer who never understood Maxwell's equations, I thought if I had a HoloLens, I would have been a better electrical engineer. Overall I feel that augmented reality is perhaps the ultimate computer," he said.

From here.

Actually, the article was entitled, "Microsoft CEO says artificial intelligence is the 'ultimate breakthrough'", but I was struck by his confession of ignorance about the foundational theory of classical electromagnetism.

Maxwell's equations

This looks bad, of course. But let's cut the CEO some slack: Maxwell's equations are notoriously unintuitive, as I observed in this post.

You can use the equations, solving them for particular physical configurations. But what picture do they give of the nature of the field(s) themselves?

What are we to make of the fact that a stationary observer of a motionless charged ball sees a static spherical electric field E, while an observer moving past that same ball sees electric and magnetic fields (E' and B')?

The magnetic field is a relativistic effect.

The charge is at rest in frame F, so this observer notes a static electric field. An observer in another frame F′ moves with velocity v relative to F, and notices the charge to move with velocity −v with an altered electric field E due to length contraction and a magnetic field B due to the motion of the charge. (Wikipedia).

That's implicit in Maxwell's equations, but don't tell me it's obvious. For that, you need to write the equations in a manifestly covariant form, but they don't teach you that in undergraduate electrical engineering.

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Oh, and he's surely right about augmented reality being the main deliverable from the current state of the art in artificial neural net technologies. The Holy Grail of AGI will be a product of mastering situated social cognition, a post for another day (but see here).

AI really is applied neurobiology

When I was researching AI back in the 1980s, we'd all heard of Geoffrey Hinton. He was the key pioneer of artificial neural nets, a field which at the time wasn't making much progress. He never turned up at the main AI conferences where we discussed logics, theorem-proving and symbolic planning programs. A different paradigm entirely.

I never set eyes on him.

Professor Hinton has had the last laugh. His work, and that of close colleagues, underpins the recent AI successes of Google (AlphaGo!), Baidu, Facebook and Microsoft. Whether it's speech recognition, automatic translation or face recognition, deep-learning neural nets are powering it along behind the scenes.

Here's Professor Hinton's recent address to the Royal Society (h/t Steve Hsu). I don't normally find time to watch other people's recommended videos, but I made an exception for this one. Hinton rather reminds me of Richard Dawkins in appearance and style. He's lucid, understated and staggeringly smart. Here he engagingly tells the story of the fall and rise again of the neural net approach to artificial intelligence.

At almost the end of the talk, he puts up this slide for almost two seconds .. and then hides it.

The "secret slide"

I'm sure he just felt it wasn't quite aligned to his audience which didn't seem packed with AI specialists.

There was always a tendency within AI which made a distinction between our language for describing agents as knowing, believing, wanting entities - using intentional, symbolic terms, and the presumed internal agent architecture which caused behaviour - and which need not involve pushing symbols around at all.

We've long been aware of the awesome computation underlying animal/human unconscious situational competences. We've long failed to replicate such abilities using 'Good Old-Fashioned AI'. Perhaps it's time to conclude, with Prof. Hinton, that the architecture which realises such capabilities really has to be that of the deep-learning neural net.

Prof. Hinton is at pains to point out that the most sophisticated current systems fall well short of human brain structure both in terms of quantity of neurons and complexity of interconnection and communication.

We should keep reminding ourselves that brains are doing important stuff at the granularity of small groups of molecules: they are the essence of nanotech.*
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* In fact, we should probably be using our best AI neural nets to figure out what our own neurons are actually doing. The massive connectivity found in brains may implement features and structures so complex as to be beyond unaided human comprehension.

[In an interesting analogy, you may recall the 'killer app' for quantum computers is said to be the simulation of quantum systems themselves, intractable with conventional computers.]