My issue with these services is they always tout these use cases like:
>"Can you make me dinner reservations?"
or
>"Can you help me plan my next vacation?"
I'd really love to better understand who is actually asking those types of questions in such a vague fashion, and what their use case is. When I'm picking something as simple as a restaurant, I typically want options, I want to read reviews, I want to consider distance, parking, attire, etc. While their AI/human trainers might be able to handle this level of complexity eventually, the actual phrasing of the question would likely be much more complex than "can you make me a dinner reservation." Doubly so for something like a vacation which has a lot more moving parts.
But I respect that I'm reflecting on a sample size of one...me. So I'd love to hear from others with more insight into the data around this. Are people actually searching with such generalized queries when it comes to tasks like this? Do most people not sweat the details of things like which restaurant to eat at, or where to spend hundreds or potentially thousands of dollars on a vacation?
I'm thinking "get me a dinner reservation next sunday with patio seating for 5 in the east village at an upscale tapas place".
As I mentioned elsewhere on this page, my thesis around conversational interfaces isn't that they start off broad and use more Q/A to refine your query. That's slow, and people are visual.
Rather, their power lies in the user being able to express a complex query in one go - which is equivalent to tapping 10-15 filters and scrolling through results - ideally combining data from sources that aren't limited to one service.
You can now execute related actions to your result set through the same interface, without needing to shift to a single purpose app that would allow you to take the action, but for most purposes, won't keep your context.
I think AI researchers and engineers tend to get too carried away with decision making, when the more valuable service is about communication of refined knowledge, which if I'm not mistaken is exactly your point. The problem has nothing to do with "how can a machine guess the right answer" but instead is all about "how can a machine refine all the options based on the intentions expressed thus far".
Anecdotally, if we'd ask a real person "where is a good place to eat" the chance we'd go there without more information is slim. And if we don't even trust people, trusting Siri will be a while.
What we're really doing with these questions is making our hunger known, and starting a conversation. We actually don't care that much about other people's thoughts, and we may not even have anything in mind yet as far as where to eat. We do care about how people feel if they are someone we care about, but the thinking part we love to do ourselves.
So to offer a service that "thinks" is rather misguided, and may even constitute a disservice. We already rejected the talking paperclip in 1996 [0]. It's failure wasn't it's intelligence, but in the value proposition itself. To have a paperclip presume to know better and to tell you what to do was not tempting. It's failure was it's existence.
Is it a glitch in the Matrix or is their pitch for Cortana identical?
> What is Cortana? Cortana is your clever new personal assistant.[1]
If I ask someone I know what's a good place to eat, the odds are actually quite high that I'll give it a try. I wouldn't have asked otherwise.
The issue here is one of trust, which is built on an individualized relationship over time. When I ask someone I know for a recommendation, I'm doing so because I already have a sense of their judgment. That's more the key here- build a history of reliable judgment. That's the goal.
Right. This is certainly one path and the path most seem to be on, and exactly the one that needs to be challenged. The key intuition here being that a judgement, which is a decision, is not an answer to a logical problem. A decision entails a will, and when our personal will is overridden by an animated paperclip, we close said program. Decision != Answer.
People don't necessarily want decisions made for them, but rather, they want assistance in making their own, or better yet, reasons to justify the decisions they've already tentatively made. "Reliable judgement" is the complete opposite of "a resource of intelligence". Certainly all of these assistants feature a little bit of both, but I keep sensing the urge towards the former. Worse yet, a decision is often treated as an abstraction that somehow justifies hiding everything that went into that decision, even though there is immense value in actually being told why. People have entire conversations over why to eat at some place as part of the process of sharing the decision to go there.
Even when used only as a resource, if only these robots wouldn't keep trying to read our minds or insist on telling us what to do. Maybe a handful of people will accept a robot's choice, but everyone loves more information.
Maybe we shouldn't be looking for some secret sauce that enables robots to make better generalized and rational decisions than humans. Maybe we should be building robots capable of assisting humans at better making their own personal and irrational decisions instead?
> Is it a glitch in the Matrix or is their pitch for Cortana identical?
No, its not a glitch that Siri, Google Now, Cortana, and now M have essentially the same pitch -- they are direct competitors intended to attach people to their respective platforms.
Thanks for helping me get to the meat of what I was trying to communicate.
It really is all about the interface and the efficiency. I have to wonder though at what point is adding all those filters more involved than checking a couple boxes and glancing at a map or some photos. I'm sure a lot of that depends on context (I can't do those things if I'm driving, but I can use voice recognition).
The other thing I'm unclear about is how such a recommendation engine can best present information about tradeoffs. In theory, each of my filters has a weighting, and that weight might be dynamic based on several other factors. Maybe I really want chinese, but the best match is further away or I know there will be lots of traffic, so I might be willing to compromise on thai, but only if they have that one dish I like. And a lot of it is seeing the options in the moment and making a snap decision. Really curious about the approaches to solve that type of problem.
> I have to wonder though at what point is adding all those filters more involved than checking a couple boxes and glancing at a map or some photos
_When the filters are across datasets and services that are hosted on different platforms, and there's no way one UI that allows you to access them._
Table timings are on OpenTable/Yelp, reviews are on Google/Yelp, traffic is on Google, rides are on Uber and Lyft, menus are on the web, there are recommendations you trust amongst your friends and blogs, and pictures on instagram - and you're on a messaging platform trying to coordinate with 4 other people.
At that point, whatever service helps you to narrow to 4 choices based on all of this data is a Godsend. It's about making decision taking easier.
> how such a recommendation engine can best present information about tradeoffs
That tradeoffs are still yours to dictate - you simply look at the results of your complex query and then use conversation/UI to refine. Faster than using 8 services to do this. Repeatedly.
For me, it's entirely "going out with friends". But that doesn't mean I'm going to leave restaurant selection to a bot. For many, people, selecting a restaurant is fun. And I bet you and your friends don't just go to some random place.
We also tend to use very subjective terms like "best," e.g., "where's the best place for food in Taipei?"
What is "best" and to whom? Ideally the software would figure this out but I'd always be wondering if it was just going to TripAdvisor and grabbing the first result.
Another problem is that we don't always know what kind of food we want. There's an urban legend that someone actually called a restaurant "I don't care" so that boyfriends would have a place to go when asking their girlfriend for dinner.
The initial example is broad, but can't this just be extended with additional questions? For example, can you tell me about dinner options that cost less than $20 per person. What are other people saying? How far away is this? It's questionable whether each of these follow up questions is actually that complex. I think you are arguing that things get hard if a user tries to put that together in one single complex query. Do people do that though?
I think the idea with a conversational interface is that it's succinct and on-demand. You receive the most relevant information directly in as simple of an interface as possible (arguably).
It's much faster for me to hit a few filters on things like prices and locations. Distance is just a simple ".2 miles away" text on the box, which shows an image and snippets of reviews. People are more and more visual.
I don't think a conversational interface _replaces_ a visual one.
It's that the initial query can be complicated, and it allows you to get into that 5-6 tier deep part of your search that you would have gotten to by using 5 filters and scrolling through 50 results.
Don't have an Echo and have never ordered groceries so not sure how they solve this one, but taking the example of "Add eggs to shopping list"...how do they handle brand options with general queries like that? Are there brand options?
I get groceries delivered weekly from Ocado in the UK, and they put together the weekly shopping list for us. Automatically.
They do so entirely based on past shopping history.
Currently the only annoyance is logging in once a week to check if there's any adjustments we'd like to make. But it's good enough that if I don't feel like it, I'll just take my chances (you can also add "always include X" and "never automatically add Y" rules, which is part of the reason why that works...) and most of the time I get what we need.
I never want to go back to putting together my own shopping list from scratch.
This is how I want these type of services to work. I don't want to have to talk to them. 99% of the time, I'd prefer them to be invisible to me, and make things that used to be an annoyance just disappear.
But the one way it could be better would be to make that one last interaction disappear more often: Not having to log in to make changes. Being able to just say out in the air that I want to add eggs, would be great, and in that case I'd want it added based on past preferences: If I've bought eggs before, and I'm not specifying, just add the quantity and brand I usually order. If an alternative I've also ordered is cheaper or on offer, ask for confirmation if I'd be happy with that instead. If I haven't bought eggs before, pick a brand based on my past overall purchase history, and ask for confirmation, or simply add some - if I'm asking to "add eggs" rather than "please recommend me some eggs for my grocery shopping", I probably don't care.
To make this useful, perhaps you could set up some kind of saved preferences. For example, let's say I'm setting up a business trip. I like hotels that are within 1 mile of the conference center, and they have to be at least 3.5 stars and up. Provided they meet those criteria, the cheapest option is acceptable. I also need a plane flight that has no more than 1 layover, and that layover cannot last longer than 90 minutes or less than 45. I am willing to pay up to 25% more for a nonstop flight. The flight must arrive the day before the conference, but it can depart on the day the conference ends.
Setting up those criteria for each individual search would be irritating and a waste of effort, as they don't change from trip to trip. However, if I could say something like "Let me tell you about my criteria for choosing a location for a business trip.", and then go into detail once, that might work. Hell, I'd be perfectly happy setting up the details on a website. Then, the next time I said "I need to set up a business trip", all it would need to ask is the conference center and the dates of the conference.
Until it supports these kinds of detailed requests, it doesn't make sense to use these kinds of services in the way they market them - you'll end up using it in the same limited way you could use Siri. For example, if you've already decided what restaurant you want, you might say "Make me a reservation at Dorsia for 7:30 this evening" instead of the examples you provided.
A lot of it is simply about learning when you know enough and when you need more information through the interactions themselves. If you have to "set things up" it seems tedious. If it's just conversing with you about the information it needs, and gradually learning your preferences, that's different.
I used to fly in to the Bay Area very often on business. At first the office manager arranging things would ask me details about which airline and which flights I'd prefer after listing the options, and which hotels, describing address and location and how near they were the office. Possibly e-mailing me a bunch of links for me to look at. But after just a few trips it was down to "is flying out on the 2.30 on Wednesday and returning on the 3.15 the following Thursday, ok? [she know when I preferred to fly, and she'd implicitly have ensured they were the right code to maximize my chance of an upgrade] Your usual hotel is full, is the Sheraton ok?" [no addresses necessary - we'd boiled it down to 2-3 preferred hotels within walking distance of the office].
I think these exmples are largely worthless also. Every time I see something like this - I all but dismiss it. It seems like the aim/value proposition is to make life easier by removing decisions from our plate, but I feel like it is exchanging decisions for frustration when it doesn't work as promised, or worry about whether the decisions the system makes will be good ones.
I actually don't want a machine to make decisions for me. I want a machine to do what I tell it to do, or present me with I formation required to make a decision.
Examples: if I need a dentist appointment or to schedule maintenance for my air conditioning, I'd like to tell a machine to set it up. Heck, I'll even tell it who to call and which days and times work for me.
If I'm looking for a restaurant, show me the options, give me their distance, top reviews, and some of their dishes. If I want reservations, I'll tell it when and for how many.
Ideally, I want a "Jarvis" from "Iron Man". I ask questions, it gives data in a digestible quantity, and then I can make a decision and tell it what to do. Obviously, such a system is not available (yet), and these inferior systems are needed in order to make progress, and get there...eventually..but sometimes I wonder if the focus is on the right outcome, or just the broad strokes cookie cutter solution that comes to mind first (restaurant reservations). Similar to how all JavaScript MVC frameworks demo a to-do app, and rails tutorials demo'd a blog (initially)...
I mean, seriously... How often do you not go out to eat because you are too lazy or busy to make a reservation? Now, how many times do you skip oil changes, or making calls to cancel your cable service, because you don't want to make time in your day to stop what you're doing, pick up the phone, and call?
100% agree. I'd refine it slightly by saying it isn't just a recommendation we want, it is presenting us with the logic under the hood in terms of HOW it made the decision--not what the decision was.
If it told me it recommended the restaurants along with commentary like "you really liked X at another place, and this place has been voted to have comparable X, plus it is close by and you've had a long day and need to get up early tomorrow" that would be super useful and help me reach my own conclusion faster.
Agree completely. I saw a similar issue with sites like Operator, Magic, etc. The requests were very vague, making me wonder, "Am I spending too much time thinking about where to order a pizza from?"
And if I know which pizza shop I want to order from, what's the benefit of adding an intermediary?
I use an intermediary for all my takeaway. Basically in the UK there are now two big intermediary sites. On one hand they are annoying to many of these businesses as they obviously take a cut including of a lot of repeat business. On the other hand, I receive an e-mail around the time I start getting hungry on Friday afternoon giving me a link to click if I want to re-order from my favourite Chinese, that lets me choose to pre-fill the order with what I usually order. It makes it a lot easier than hunting around for the phone number or their website and placing an order manually.
That's why I use an intermediary. If that intermediary was being able to just say "I'd like my usual pizza/Chinese/burrito, but instead of X I'd like Y" and just have it confirm what it was about to do, I'd love that.
If want something new, or I'm somewhere I haven't been before, that's different - then I'll be spending time looking at the menu etc.
I guess there could be "Hey M, order my usual from the pizza place" or something like that.
But until it elevates from 'digital assistant' level to just 'assistant' (ie. do all the work and just confirm with me before booking) it may not take off as they expect it to
Have you ever used a concierge service either at a hotel or over the phone? It usually takes a form of a back and forth conversation to identify what you really want.
That's the difference between talking to a real person (or good NLP) and a search query.
I guess part of this is that I'd prefer the concierge to hand me a list of restaurants than have to have a whole conversation about what the options are. I don't want expertise, I want curated information.
> When I'm picking something as simple as a restaurant, I typically want options, I want to read reviews, I want to consider distance, parking, attire, etc.
For me, a lot of what you're doing here is the work that should be done by a machine. Considering "distance, parking, attire, etc." is basically what we have simplex method for.
But I agree the questions seem very vague in the context. To run such errands successfully, the program would have to know much more about your preferences than current iterations of personal assistant software do. And/or hold a dialog with you, asking for details and proposing options.
"Can you make me dinner reservations?" would lead to a response like "Any preferences on the type of food and location?"
Over time they learn your preferences so they don't need to ask location for example next time.
Your right though people aren't likely asking such generic things in the first place, but rather something like "can you book me a great mexican place for dinner tonight, 2 people, has parking and casual attire somewhere with great yelp reviews"
Then they send you the best options they found (and the benefits of each one and price range) then you reply back option 1 and they book it.
This is a great question, and probably the question that Facebook wants to answer by rolling out this experiment. It sounds like some (most?) of M's answers are provided by humans and/or highly-customized apps. This release could be more of a Wizard of Oz experiment so that they can drill down on use cases and create more effective affordances.
Very valid and am glad am not the only one who thinks on similar lines. Again, no intention of trolling but I'll be happy if an AI system understood a narrow question "I want to eat at the nearest available Lebanese restaurant" and gave some options.
Bassed on my understanding of semantics and Knowledge engineering, this is doable.
Exact same feeling, but I don't know how representative that is of the general population. I don't use tripadvisor because I can't afford to talk interactively to a travel agent, I prefer to use tripadvisor.
>"Can you make me dinner reservations?"
or
>"Can you help me plan my next vacation?"
I'd really love to better understand who is actually asking those types of questions in such a vague fashion, and what their use case is. When I'm picking something as simple as a restaurant, I typically want options, I want to read reviews, I want to consider distance, parking, attire, etc. While their AI/human trainers might be able to handle this level of complexity eventually, the actual phrasing of the question would likely be much more complex than "can you make me a dinner reservation." Doubly so for something like a vacation which has a lot more moving parts.
But I respect that I'm reflecting on a sample size of one...me. So I'd love to hear from others with more insight into the data around this. Are people actually searching with such generalized queries when it comes to tasks like this? Do most people not sweat the details of things like which restaurant to eat at, or where to spend hundreds or potentially thousands of dollars on a vacation?
Not trolling, serious question.