Be Smart, Use Dumb Devices

The latest news in the world of Things Which Are Too "Smart" For Their Users’ Good is that Facebook have released a new device in their Portal range: a video camera that sits on your TV and lets you make video calls via Facebook Messenger and WhatsApp (which is also owned by Facebook).

This is both a great idea and a terrible one. I am on the record as wanting a webcam for my AppleTV so that I could make FaceTime calls from there:

In fact, I already do the hacky version of this by mirroring my phone’s screen with AirPlay and then propping it up so the camera has an appropriate view.

Why would I do this? One-word answer: kids. The big screen has a better chance of holding their attention, and a camera with a nice wide field of view would be good too, to capture all the action. Getting everyone to sit on the couch or rug in front of the TV is easier than getting everyone to look into a phone (or even iPad). I’m not sure about the feature where the camera tries to follow the speaker; in these sorts of calls, several people are speaking most of the time, so I can see it getting very confused. It works well in boardroom setups where there is a single conversational thread, but even then, most of the good systems I’ve seen use two cameras, so that the view can switch in software rather than waiting for mechanical rotation.

So much for the "good idea" part. The reason it’s a terrible idea in this case is that it’s from Facebook. Nobody in their right mind would want an always-on device from Facebook in their living room, with a camera pointed at their couch, and listening in on the video calls they make. Facebook have shown time and time and time again that they simply cannot be trusted.

An example of why the problem is Facebook itself, rather than any one product or service, is the hardware switch for turning the device’s camera off. The highlight shows if the switch is in the off position, and a LED illuminates… to show that the camera and microphone are off.

Many people have commented that
this setup looks like a classic dark pattern in UX, just implemented in hardware. My personal opinion is that the switch is more interesting as an indicator of Facebook’s corporate attitude to internet services: they are always on, and it’s an anomaly if they are off. In fact, they may even consider the design of this switch to be a positive move towards privacy, by highlighting when the device is in "privacy mode". The worrying aspect is that this design makes privacy an anomaly, a mode that is entered briefly for whatever reason, a bit like Private or Incognito mode in a web browser. If you’re wondering why a reasonable person might be concerned about Facebook’s attitude to user privacy, a quick read of just the "Privacy issues" section of the Wikipedia article on Facebook criticism will probably have you checking your permissions. At a bare minimum, I assume that entering "privacy mode" is itself a tracked event, subject to later analysis…

Trust, But Verify

IoT devices need a high degree of trust anyway because of all the information that they are inherently privy to. Facebook have proven that they will go to any lengths to gather information, including information that was deliberately not shared by users, process it for their own (and their advertising customers’) purposes, and do an utterly inadequate job of protecting it.

The idea of a smart home is attractive, no question – but why do the individual devices need to be smart in their own right? Unnecessary capabilities increase the vulnerability surface for abuse, either by a vendor/operator or by a malicious attacker. Instead, better to focus on devices which have the minimum required functionality to do their job, and no more.

A perfect example of this latter approach is IKEA’s collaboration with Sonos. The Symfonisk speakers are not "smart" in the sense that they have Alexa, Siri, or Google Assistant on board. They also do not connect directly to the Internet or to any one particular service. Instead, they rely on the owner’s smartphone to do all the hard work, whether that is running Spotify or interrogating Alexa. The speaker just plays music.

I would love a simple camera that perched on top of the TV, either as a peripheral to the AppleTV, or extending AirPlay to be able to use video sources as well. However, as long as doing this requires a full device from Facebook1 – or worse, plugging directly into a smart TV2 – I’ll keep on propping my phone up awkwardly and sharing the view to the TV.


  1. Or Google or Amazon – they’re not much better. 

  2. Sure, let my TV watch everything that is displayed and upload it for creepy "analysis".3 

  3. To be clear, I’m not wearing a tinfoil hat over here. I have no problem simply adding a "+1" to the viewer count for The Expanse or whatever, but there’s a lot more that goes on my TV screen: photos of my kids, the content of my video calls, and so on and so forth. I would not be okay with sharing the entire video buffer with unknown third parties. This sort of nonsense is why my TV has never been connected to the WiFi. It went online once, using an Ethernet cable, to get a firmware update – and then I unplugged the cable. 

New York, New York

This has been a great week in New York City. I was in town for New Hire Technical Training, or NHTT to its friends, which means pretty intense ten-hour days on top of the weeks of prerequisites to even get to this point – but it’s New York Freaking City, so I still took time to wander around. One day I got a step count in the 20ks!

Anyway, here are some shots from the week.

Discoverability

As more and more devices around us sprout microphones and "smart" assistant software that listens for commands, various problems are emerging. Much attention is lavished on the Big Brother aspects of what amounts to always-on ambient surveillance, and that is indeed a development that is worth examining. However, today I would like to focus on another aspect of voice-controlled user interfaces: when a system has no easy way of telling you what its capabilities are – how do you know what to ask it?

The answer to this question entails discoverability, and I would like to illustrate this somewhat abstract concept with a picture of a tap. This particular tap lives in my employers’ newly refurbished London office, and I challenge you to work out how to get sparkling water from it.

The answer is that you press both taps – and now that I’ve told you, you may perhaps notice the pattern of bubbles along the bottom of the two taps. However, without the hint, I doubt you would ever have worked it out.

Siri, Alexa, Cortana1, and their ilk suffer from the same problem – which is why most people tend to use them for the same scant handful of tasks: setting timers, creating reminders, and playing music. Some users are willing to experiment with asking them to do various things, but most of us have enough going on in our lives that we can’t take the time to talk to very stupid robots unless we have a reasonable certainty of our requests being understood and acted upon.

Worse, even as existing capabilities improve and new ones are added, users generally stick to their first impressions. If they tried something a couple of years ago and it didn’t work then, as far as they’re concerned it doesn’t work, even if that particular capability has been added in the meantime.

I generally find out about new Siri features from Apple-centric blogs or podcasts, but that’s only because I’m the sort of person who goes looking for that kind of thing. I use Siri a fair amount, especially while driving, although AirPods have made me somewhat more willing to speak commands into thin air, so I do actually take advantage of new features and improved recognition. For most people, though, Siri remains the butt of jokes, no matter how much effort Apple puts into it.

This is not a competitive issue, either; almost everyone I know with an Alexa just treats it as a radio, never using any other skills beyond the first week or so of ownership.

The problem is discoverability: short of Siri or Alexa interrupting you ("excuse me, have you heard the good news?"), there isn’t any way for users to know what they can do.

This is why I am extremely sceptical of the claims that voice assistants are the next frontier. Even beyond the particular issues of people in an open-plan office all shouting at their phones, and assuming perfect recognition by the AIs2 themselves, voice is an extremely low-bandwidth channel. If my hands and eyes are available, those are far better input and output channels than voice can ever be. Plus, graphical user interfaces are far better able to guide users to discover their capabilities, without degenerating into phone menu trees.

Otherwise, you have to rely on the sorts of power users who really want sparkling water and are willing to spend some time and effort on figuring out how to get it. Meanwhile, everyone else is going to moan and gripe, or bypass the tap entirely and head for the bottled water.


  1. I find it significant that autocorrect knows the first two, but not the third. As good an indication as any of their relative market penetration. 

  2. Not actually AI. 

Don't Blame The User

It would be easy to write a blog post about every single XKCD strip, so I try not to – but the latest one drives at something very interesting in infosec.

Some of the default infosec advice that is always given out is to avoid reusing passwords on different sites. This is good advice as far as it goes, but it misses one key aspect. Too many sites force people to create accounts for no good reason ("create an account to use our free wifi"), and so people use throwaway passwords, and reuse them across many of these low-risk sites. In the XKCD example above, if someone cracks the Smash Mouth message boards, maybe they get to reuse the password to gain access to the Limp Bizkit boards, but ideally they won’t get access to Venmo, because that not only has a different, higher-grade password, but is also secured by 2FA1.

The good news is that it’s becoming easier than ever to generate secure passwords and avoid reusing them. If you’re an Apple user, the iCloud Keychain is built right into both iOS and macOS, and will generate and remember secure passwords for you, securing them with FaceID or TouchID. There are of course any number of third-party options as well, but the point is that security needs to be easy. People who care about security will sign for Have I Been Pwned; general users just trying to get through their day will not.

The first priority is making it work at all, the second is making it usable; regrettable as it may be, security comes after those primary concerns. The easier it is for users to do the right thing, the more likely it is that they will do it. Browbeating them after a breach because they didn’t jump through precisely the right hoops in exactly the right sequence is not helpful. What will help is putting the effort into helping them up front, including in the service design itself.

Previously, previously.


  1. Note, I have no idea whether Venmo actually supports 2FA; not being in the US, I don’t / can’t use it. For "Venmo", read "online banking" or whatever other high-security example. 

Once More On Privacy

Facebook is in court yet again over the Cambridge Analytica scandal, and one of their lawyers made a most revealing assertion :

There is no invasion of privacy at all, because there is no privacy

Now on one level, this is literally true. Facebook's lawyer went on to say that:

Facebook was nothing more than a "digital town square" where users voluntarily give up their private information

The issue is a mismatch in expectations. Users have the option to disclose information as fully public, or variously restricted: only to their friends, or to members of certain groups. The fact that something is said in the public street does not mean that the user would be comfortable having it published in a newspaper, especially if they were whispering into a friend’s ear at the time.

Legally, Facebook may well be in the right (IANAL, nor do I play one on the Internet), but in terms of users’ expectations, they are undoubtedly in the wrong. However, for once I do not lay all the blame on Facebook.

Mechanisation and automation are rapidly subverting common-sense expectations in a number of fields, and consequences can be wide-reaching. Privacy is one obvious example, whether it is Facebook’s or Google’s analysis of our supposedly private conversations, or facial recognition in public places.

For an example of the reaction to the deployment of these technologies, the city of San Francisco, generally expected to be an early adopter of technological solutions, recently banned the use of facial recognition technology. While the benefits for law enforcement of ubiquitous automated facial recognition are obvious, the adoption of this technology also subverts long-standing expectations of privacy – even in undoubtedly public spaces. While it is true that I can be seen and possibly recognised by anyone who is in the street at the same time as me, the human expectation is that I am not creating a permanent, searchable record of my presence in the street at that time, nor that such a record would be widely available.

To make the example concrete, let’s talk for a moment about numberplate recognition. Cars and other motor vehicles have number plates to make them recognisable, including for law enforcement purposes. As technology developed, automated reading of license plates became possible, and is now widely adopted for speed limit enforcement. Around here things have gone a step further, with average speeds measured over long distances.

Who could object to enforcing the law?

The problem with automated enforcement is that it is only as good as it is programmed to be. It is true that hardly anybody breaks the speed limit on the monitored stretches of motorway any more – or at least, not more than once. However, there are also a number of negative consequences. Lane discipline has fallen entirely by the wayside since the automated systems were introduced, with slow vehicles cruising in the middle or even outside lanes, with empty lanes on the inside. The automated enforcement has also removed any pressure to consider what is an appropriate speed for the conditions, with many drivers continuing to drive at or near the speed limit even in weather or traffic conditions where that speed is totally unsafe. Finally, there is no recognition that, at 4am with nobody on the roads, there is no need to enforce the same speed limit that applies at rush hour.

Human-powered on-the-spot enforcement – the traffic cop flagging down individual motorists – had the option to modulate the law, turning a blind eye to safe speed and punishing driving that might be inside the speed limit but unsafe in other ways. Instead, automated enforcement is dumb (it is, after all, binary) and only considers the single metric it was designed to consider.

There are of course any number of problems with a human-powered approach as well; members of ethnic or social minorities all have stories involving the police looking for something – anything – to book them for. I’m a straight white cis-het guy, and still once managed to fall foul of the proverbial bored cops, who took my entire car apart looking for drugs (that weren’t there) and then left me by the side of the road to put everything back together. However, automated enforcement makes all of these problems worse.

Facial recognition has documented issues with accuracy when it comes to ethnic minorities and women – basically anyone but the white male programmers who created the systems. If police start relying on such systems, people are going to have serious difficulties trying to prove that they are not the person in the WANTED poster – because the computer says they are a match. And that’s if they don’t just get gunned down, of course.

It is notoriously hard to opt out of these systems when they are used for advertising, but when they are used for law enforcement, it becomes entirely impossible to opt out, as a London man found when he was arrested for covering his face during a facial recognition trial on public streets. A faulty system is even worse than a functional one, as its failure modes are unpredictable.

Systems rely on data, and data storage is also problematic. I recently had to get a government-issued electronic ID. Normally this should be a simple online application, but I kept getting weird errors, so I went to the office with my (physical) ID instead. There, we realised that the problem was with my place of birth. I was born in what was then Strathclyde, but this is no longer an option in up-to-date systems, since the region was abolished in 1996. However, different databases were disagreeing, and we were unable to move forward. In the end, the official effectively helped me to lie to the computer, picking an acceptable jurisdiction in order to move forwards in the process – and thereby of course creating even more inaccuracies and inconsistency. So much for "the computer is always right"… Remember, kids: Garbage In, Garbage Out!

What, Me Worry?

The final argument comes down, as it always does with privacy, to the objection that "there’s nothing to fear if you haven’t done anything wrong". Leaving aside the issues we just discussed around the possibility of running into problems even when you really haven’t done anything wrong, the issue is with the definition of "wrong". Social change is often driven by movement in the grey areas of the law, as well as selective enforcement of those laws. First gay sex is criminalised, so underground gay communities spring up. Then attitudes change, but the laws are still on the books; they just aren’t enforced. Finally the law catches up. If algorithms actually are watching all of our activity and are able to infer when we might be doing something that’s frowned upon by some1, that changes the dynamic very significantly, in ways which we have not properly considered as a society.

And that’s without even considering where else these technologies might be applied, beyond our pleasant Western bubble. What about China, busy turning Xinjiang into an open-air prison for the Uyghur minority? Or "Saudi" Arabia, distributing smartphone apps to enable husbands to deny their wives permission to travel?

Expectations of privacy are being subverted by scale and automation, without a real conversation about what that means. Advertisers and the government stick to the letter of the law, but there is no recognition of the material difference between surveillance that is human-powered, and what happens when the same surveillance is automated.


Photo by Glen Carrie and Bryan Hansonvia Unsplash


  1. And remember, the algorithms may not even be analysing your own data, which you carefully secured and locked down. They may have access to data for one of your friends or acquaintances, and then the algorithm spots a correlation in patterns of communication, and associates you with them. Congratulations, you now have a shadow profile. And what if you are just really unlucky in your choice of local boozer, so now the government thinks you are affiliated with the IRA offshoot du jour, when all you were after was a decent pint of Guinness? 

Turning Over A New Leaf

Yesterday was the LinkedIn equivalent of a birthday on Facebook: a new job announcement. I am lucky enough to have well-wishers1 pop up from all over with congratulations, and I am grateful to all of them.

With a new job comes a new title – fortunately one that does not feature on this list of the most ridiculous job titles in tech (although I have to admit to a sneaking admiration for the sheer chutzpah of the Galactic Viceroy of Research Excellence, which is a real title that I am not at all making up).

The new gig is as Director, Field Initiatives and Readiness, EMEA at MongoDB.

Why there? Simply put, because when Dev Ittycheria comes calling, you take that call. Dev was CEO at BladeLogic when I was there, and even though I was a lowly Application Engineer, that was a tight-knit team and Dev paid attention to his people. If I have learned one thing in my years in tech, it’s that the people you work with matter more than just about anything. Dev’s uncanny knack for "catching lightning in a bottle", as he puts it, over and over again, is due in no small part to the teams he puts together around him – and I am proud to have the opportunity to join up once again.

Beyond that, MongoDB itself needs no presentation or explanation as a pick. What might need a bit more unpacking is my move from Ops, where I have spent most of my career until now, into data structures and platforms. Basically, it boils down to a need to get closer to the people actually doing and creating, and to the tools they use to do that work. Ops these days is getting more and more abstract, to the point that some people even talk about NoOps (FWIW I think that vastly oversimplifies the situation). In fact, DevOps is finally coming to fruition, not because developers got the root password, but because Ops teams started thinking like developers and treating infrastructure as code.

Between this cultural shift, and the various technological shifts (to serverless, immutable infrastructure, and infrastructure as code) that precede, follow, and go along with them, it’s less and less interesting to talk about separate Ops tooling and culture. These days, the action is in the operability of development practices, building in ways that support business agility, rather than trying to patch the dam by addressing individual sources of friction as they show up.

More specifically to me, my particular skill set works best in large organisations, where I can go between different groups and carry ideas and insights with me as I go. I’m a facilitator; when I’m doing my job right, I break information out of silos and spread it around, making sure nobody gets stuck on an island or perseveres with some activity or mode of thinking that is no longer providing value to others. Coming full circle, this fluidity in my role is why I tend to have fuzzy, non-specific job titles that make my wife’s eyes roll right back in her head – mirroring the flow I want to enable for everyone around me, whether colleagues, partners, or users.

It’s all about taking frustration and wasted effort out of the working day, which is a goal that I hope we can all get behind.

Now, time to blow away my old life…


  1. Incidentally, this has been the first time I’ve seen people use the new LinkedIn reactions. It will be interesting to watch the uptake of this feature. 

Piercing The Clouds

Now here’s an interesting document: "A Measurement Study of Server Utilization in Public Clouds". Okay, it’s from 2011, but otherwise seems legit.

Basically it’s a study of total CPU utilisation in both AWS and Azure (plus a brief reference to GoGrid, a now-defunct provider acquired by Datapipe, who in turn were acquired by Rackspace). The problem is that very few people out there are doing actual studies like this one; it’s mostly comparisons between on-prem and remote clouds, or between different cloud providers, rather than absolute utilisation. However, it’s interesting because it appears to undermine one of the biggest rationales for a move to the cloud: higher server utilisation.

Note that Y-axis: utilisation is peaking at 16%.

The study’s conclusion is as follows:

Apparently, the cost of a cloud VM is so low that some users choose to keep the VM on rather than having to worry about saving/restoring the state.

I wonder if this study would bring any substantially different results if repeated in 2019, with all the talk of serverless and other models that are much less dependent on maintaining state. It is plausible that in 2011 most workloads, even in public clouds, were the result of "lifting and shifting" older architectures onto new infrastructure. The interesting question would be, how many of those are still around today, and how many production workloads have been rearchitected to take advantage of these new approaches.

This is not just an idle question, although there is plenty of scope for snarkily comparing monolithic VMs to mainframes. Cloud computing, especially public cloud, has been able to claim the mantle of Green IT, in large part because of claims of increased utilisation – more business value per watts consumed. If that is not the case, many organisations may want to re-evaluate how they distribute their workloads. Measuring processor cycles per dollar is important and cannot be ignored, but these days the big public cloud providers are within shouting distance of one another on price, so other factors start to enter into the equation – such as environmental impacts.


Image by Samuel Zeller via Unsplash