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> If the person asking the question lives in Ohio, they may actually be talking about London OH (or Dublin OH).

I would seriously doubt this assumption. Why on earth should someone living in a state specifically ask for the local time in a different location within that same state?

On the contrary, this context information would make it much more likely that the person actually meant "London, England". Except if there is a timezone border going through the state, of course.

However, I obviously agree with your general point regarding the severe limitations of what we currently call "AI" and how little "intelligence" there actually is.

> Why on earth should someone living in a state specifically ask for the local time in a different location within that same state?

True, and that's another contextual layer to deal with: that e.g. the state of Ohio is in a single timezone and that - why on Earth should someone ask the time within the same timezone? - like you said. And then there may be contextual exceptions even from this rule...

you might not know where the timezone boundary is - they move, or you're new to the area. alternatively, there could be a daylight savings boundary in between, so it is only in the same timezone for half the year.

the fact that americans are inclined to say the state name as part of the name of a place could also help - since they might say london ohio, london might be more likely to mean the real london.

Flipping this around a bit: if someone in England asked "what's the time in London?" should Siri assume that they're talking about London in Ohio or Ontario? Everyone in England is on GMT, so they don't need to do timezone conversions to London time.

There's an extremely long-standing convention of referring to timezones by the major or capital city within that timezone, so Siri should of course assume that they're talking about London in England. In fact, this is probably more or less the correct, canonical way to ask this - asking about GMT would not give you the correct answer, since England is currently on BST which is GMT+1. Needless to say, this argument would not apply to asking about anything else about London. Context is complicated.

For similar reasons, anyone who asks for the time in Boston probably means Eastern Time regardless of how far they are from Lincolnshire, though I think the more usual and canonical way of referring to that is New York time.

Pedantic: London is currently in British Summer Time, not GMT (which it is in the winter)

I'd expect it to ask the first time around, and then remember the answer afterwards.

There are many European countries that have the same timezone, but I don't remember all of them always, despite living in Europe.

In this case it is totally normal for someone living in Netherlands to ask the time for a polish city.

> Why on earth should someone living in a state specifically ask for the local time in a different location within that same state?

Who said they were in that state when asking? People travel.

True. So substitute "living" with "currently located in". Makes the problem of correctly considering the context of that question just even more complicated ;-)

I find it unlikely that someone in that scenario would ask "What time is it in London?" rather than "What time is it in Ohio?"

I ask for the time in SF or LA all the time, rather than the time in California. Regardless, it's not hard to find cases in the same state that cross timezone boundaries. Cottonwood, AZ vs Cottonwood, AZ 86503 (on Navajo time) is an example.

SF and LA are major cities. London, OH is not.

I assume it triggers just on location, not in context of a time zone. I think Siri just hears tell me something about "location" and then just defaults to nearest.

> Why on earth

Just use your imagination a bit.

Maybe I live in state X at location Y while my parents live at location Z in the same state, about 250 miles away from me, maybe there’s a serious storm where I live and I wonder if I need to check on my elderly parents?

But you'd still be in the same time zone, no? For different queries, like the one you mentioned, that might be reasonable, but asking for the time in London means the assistant should infer England's time zone, if you're in Ohio.

Unless you live in a state like Nebraska that spans across multiple time zones…

True, there are definitely edge cases to account for. Maybe the problem is these AI assistants are trying to make everything location-aware when that may not always be the desired behavior. If there are ambiguities the assistant could ask you to clarify, but that might make for a worse UX.

Or answer both, like a human would do: "It's 3pm in London/England and 9am in London/Ohio"

> Why on earth should someone living in a state specifically ask for the local time in a different location within that same state?

Because they want to know what time it is in a different location.

14 states have more than one time zone. Do you know which ones?

> Do you know which ones?

No and that’s irrelevant trivia. What I know is if the state I live in is on that list. Oregon and it is. Don’t care what the other 13 are if I’m asking for a time in the state I live in.

The point is that just because you know the state doesn’t mean you know the time. They’re unrelated. It is reasonable for a person in Portland to ask what time it is in Ontario. They may know there are two time zones around eastern Oregon but where is the line?

Idaho is the same way. What time is it in Riggins? I’m from Idaho and I don’t even know the answer to that question. It’s a reasonable thing to ask siri.

That's a harder question. The important question here is "does your state have more than one time zone?"

No, it isn't important. What's important is how to answer the question that was asked. The number of time zones in a state has nothing to do with the time in a location. You just need to disambiguate what location is the subject of the question.

Well, it's no less important than this.

"14 states have more than one time zone. Do you know which ones? "

The point I was making there is not all states have one time zone so it is reasonable to think someone could ask for the time somewhere else because they don’t know what time it is there. Even if that somewhere else is in the same state.

I had hoped that would also demonstrate that the solution here is to just answer what was asked instead of saying “that’s not something people would ask.”

They would ask that and if you are designing a system based on what you think users won’t do then you’re gonna have a bad time.

All of these situations are fairly complicated. So the best thing to do ( even for a human assistant ) is to ask more questions. That is the best way to get clarification rather than just trying to figure out what the context is. The assistant should be able to ask a simple question: "Are you talking about the London in UK or Ohio?"

The problem is, for some subset of people, the question is ambiguous. Thus we can reduce the problem to finding that subset and asking additional questions only in those cases.

Exactly. And what about if I initially DO specify it's London Ontario that I'm interested in but five minutes later I ask again, referring to it simply as "London".. shouldn't a "better Siri" come back with 'assuming you still mean London Ontario, it's...' ?

I think it's possible that general acceptance of these non-AI gimmicks being referred to as "AI" will end up pushing genuine progress in true AI further into the future.

Agreed. These solutions seems gimmicky. AI as it is today is really a chain of "if"s. I think aside from some amazing results in niche areas, so much of the attention to ML in general (and DL in particular) is just due to marketing. It's a bubble in many cases, but since everyone is doing it, companies decide to do it as well.

I have worked on that problem recently, and yes it is really hard.

You will be surprised on how many cities are named 'San francisco' in the world : https://en.wikipedia.org/wiki/San_Francisco_(disambiguation)

I often think city names must constitute some part of their citizens' identity. How is living in a fake San Francisco pleasant for people who live there?

I think you're making basically the same mistake that Gruber is in the article, and that all "location based services" are making. The context isn't the current location, it's where people's attention is.

To take Gruber's example, if you had an office in London Ontario, were talking about setting up a video call, then asked your assistant "what time is it in London", and they picked London England because it's the most famous, you'd question how smart they were.

The context is not where you are, or which "London" is largest or most popular or least driving distance away or where you grew up or where you lived once, the context is why you are asking about the time in London, it's all of the present brain/attention/conversation/local state bundled together.

> you'd question how smart they were.

If I'm physically in a city named London, and you ask me literally "what is the time in London" that's actually an ambiguous question. Why would you specify the name of the place you're currently in? Typically someone in that instance would just ask "What time is it?"

I don't hire people to make "educated guesses" on my behalf. If they detect an ambiguity then I expect them to initiate a dialog that resolves that, not just blithely pick the first thing that comes to their mind.

> If I'm physically in a city named London,

But Gruber is not in London. If he was, perhaps we'd have a discussion about what the right answer might have been, maybe we need some more clarity, that kind of stuff. If I ask a stranger outside (well, if I did before everyone isolated themselves) they would immediately give me the time in London, England, and if I actually wanted the time in Ohio I would have to clarify myself.

> I don't hire people to make "educated guesses" on my behalf.

Of course you do. Do you really want people asking you questions all day when there could be any ambiguity?

Anyone want to guess where this sign is located?

https://imgur.com/XyTJHEc

Try this sign pointing to Mecca https://thesearchforbeauty.files.wordpress.com/2012/03/img_0...

I wonder if it actually points at Mecca…

It points to the town of Mecca which is close to the Salton Sea in Southern California.

Looks to be in Kentucky. Has both a Paris and a London, only 90 miles apart, so it's easy enough to pick a point on highway 64 that would be nearer to Paris either coming from Louisville or Huntington. Impossible to know which direction though without more context.

As a non-American, can someone explain why there are US cities with the exact same names as cities in Europe, Egypt, Greece, etc.?

Because settlers from Europe came to America and didn't give af what the Indians called their land. So they named places after ones they knew; New York, New England, Boston.

Toronto, Ontario, Niagara, Ottawa, Canada, Mississauga.

Canada kept a few.

I guess mississippi is one but most US places have white names.

Hamilton?

Heading west from Clappison's corners near Waterdown.

Specifically: https://goo.gl/maps/LidB2yoxMP9pjpXJ7

Lol look at that, a London and Paris right next to each other in Ontario too... nicely done.

in the US, based on the sign style and the road striping, and the drainage grate

On the side of the 403.

somewhere near Versailles, KY ;)

I wonder which will come first: AI that is truly able to teach itself about our world, or that we are able to define algorithms or otherwise figure out software solutions to most of these these context problems. Of course, if an AI is intelligent enough that problem solves itself.

To me it seems that developing AI on that level will be here sooner than developing solutions to many context problems, given the difficulty the best funded algorithms in the world have answering this question which we humans see as very simple.

That's exactly what gave rise to the first "AI Winter". People had to hard-code things. But with NN and esp. Deep Learning, they thought there's no need to write programs for pattern recognition anymore; the "AI" just learns it on its own.

That wishful thinking has turned out to be dangerous tho, as we have moved towards an ML-dominated world where we don't even know how the ML algorithms produce specific results.

Add that to their bizarre behavior (like this example with Siri) and you'll realize chances of another AI Winter are not low. If we have to develop solutions to many context problems one by one, that may reduce so much of the hype and interest in "AI". We'd be basically back to square one.

> We'd be basically back to square one.

But with better tools! It might not be going from 0 to 1, but going from 0.1 to 0.2 is still progress.

It is THE area people have been working on in AI.

Multi-hop reasoning models have started working surprisingly well. ie. reasoning over multiple levels and conditions.

Common sense reasoning is also getting a lot better. By having huge knowledge bases, the model can actually learn some degree of human like general purpose context. Such as, returning the time at the London which has the most similarity with the user's hidden representation.

There's a higher-order set of contexts as well. Everyone in the conversation (the asker and the answerer) knows that "London" likely means "London, UK" - that's the Bayesian default. So the if the asker wants to inquire about London, Ontario (and they are not continuing a previous conversation about London, Ontario), they are very likely to be explicit in their ask: "What's the time in London, Ontario?"

The asker has a mental model of the answerer's default contexts, and if their question is likely to be ambiguous in those default contexts, they are more likely to be explicit in their ask. The converse is also true - if the asker is not explicit about which London, that's actually a signal to the answerer to lean even harder on default contexts and best guesses.

Humans do this without even thinking because though culture and conversation we are quick to arrive at shared mental models and lean on shorthands "in the other person's head". AI not only doesn't have it's own context, it doesn't have an estimate of it's user's context and where the two might differ.

I disagree. Should the resident of London, Ontario say it every time to a virtual assistant about the weather when it should be obvious they are interested in the place of residence? And so on, all the same context layers apply (British expat in London, Ontario, etc.)

If they were somehow calling a global hotline that could answer arbitrary questions for free, then yes, I suspect someone in Ontario would still clarify. If it was a local hotline, maybe not.

Which is Siri?

Some additional variations:

What if you were calling an individual human personal assistant who knew you lived in London, Ontario?

What if you had previously clarified to this person that when you said London, you meant London, Ontario?

I think both of these questions ought to be relevant to the digital personal assistants that we're creating.

How about asking for context if it's not clear? Any reasonable human assistant would ask if the context is not clear (enough).

Obviously virtual assistants should ask for clarifications. Now imagine every time you ask for the time, weather or a flight to London and you always mean only London UK, imagine how annoying that can be. Makes me wonder if VA's are more productive in such cases compared to typing.

"The time in London, England, is 8:23pm."

"No, I meant the time in London, Ontario"

"Sure. The time in London, Ontario, is 3:23pm."

You start by doing a best guess, and actually listening for a correction. For other kinds of requests, you reply with a best guess and ask for confirmation or for clarifying questions.

Hard, yes. Not impossible.

Right. A good test for a conversational AI is whether it could perform the Abbott & Costello “Who’s on First” sketch with you. It should make assumptions where the characters in the sketch make assumptions, and ask questions borne from confusion where the characters do.

"The average time in London is 5.53 pm"

I mentioned in another comment that with Siri, this exchange does work:

“What time is it in London?”

... gives answer for London Ontario

“No, London England”

... gives answer for England

However there’s no memory to this; the same thing happens next time you ask.

The problem can be reduced to finding the subset of people for which the question is not ambiguous (or the analogous).

The solution for it is, sadly, more data. So I imagine if Google or Apple can listen, "see" and has access to your every electronic communication do. They could eventually build a model that "knows" everything about you. I am pretty sure we have the technology to do it. But the privacy implications for this is terrifying.

> The solution for it is, sadly, more data.

I don't see why that would be necessary, since a human does not need to know everything about you or have access to everything you've ever communicated to anyone to guess accurately that when you ask about "London" you probably mean London, England.

>to guess accurately that when you ask about "London" you probably mean London, England.

It depends on your circles/bubble and the context.

Sure, for me and almost certainly the majority of people the majority of the time, assuming London = London, England is almost certainly the correct disambiguation. However, maybe not someone in Ontario or Ohio asking a question about "London." And I expect that the person who sees London, England as this far away place they certainly don't have regular questions about would find that always being the default annoying.

> It depends on your circles/bubble and the context.

But not on the intimate personal details and communications of the individual person, which was what the post I was responding to was about. Sure, there are going to be circumstances where London, England is not the most likely guess, but you don't need to have access to someone's entire personal history to know what those circumstances are, since a human can spot those circumstances without having that knowledge.

> The solution for it is, sadly, more data.

The problem is these "AI"s are plain stupid. The solution for it is moving on from gimmicky and hacky solutions to true AI.

> This example illustrates how difficult AGI is and how far we are from it.

Does it? AGI is very difficult, but I think this example only illustrates that Siri is kinda bad, given that DDG, Google, Alexa, and Bing all got it right.