No one really wants a good dishwasher review. And they'll never get one, either, because a review is too easy to fake.

What we all really want is a good _dishwasher_, and word of mouth review is the tried and true method that people use to approximately measure how good a dishwasher is.

“What's a good dishwasher? I dunno… 'Hey Bob, how's your dishwasher treating you?'”

I think we'll either fall back on real word of mouth (which is *incredibly* difficult to fake, unless you can clone my friends) or we'll solve the problem at a deeper level by mashing up a service that queries the Maytag repair ticket database

It's a problem that really is begging us to cut out the middleman – it just needs a few companies who decide that they are going to be transparent and honest as part of their customer service strategy.

It just doesn't make sense to refer to humans as 'the most advanced AI'. That defies the very meaning of the term.

You're right that it's a game: this problem is entirely social, and because of that, I don't think it will end, however smart the tools get. You can think of it as the problem of building a model of what a 'good' dishwasher result is.

The modeling tools for forgery get smart just as quickly as the tools for detection – they're the same problems! If the answer to that is, “We should just let Google have all the good tools”… well, that's not going to happen.

Where this is going, of course, is that eventually fake dishwasher review sites will be composed of coherent English dishwasher reviews that are indistinguishable from real reviews in every possible way. Except that they're fake.

The problem is social; it's that there's someone out there who is willing to lie and deceive us to make a buck.

But that's a *really* hard problem to solve, so I guess we're left with technical band-aids that will, eventually, peel off.

No one really wants a good dishwasher review. And they'll never get one, either, because a review is too easy to fake.

What we all really want is a good _dishwasher_, and word of mouth review is the tried and true method that people use to approximately measure how good a dishwasher is.

“What's a good dishwasher? I dunno… 'Hey Bob, how's your dishwasher treating you?'”

I think we'll either fall back on real word of mouth (which is *incredibly* difficult to fake, unless you can clone my friends) or we'll solve the problem at a deeper level by mashing up a service that queries the Maytag repair ticket database

It's a problem that really is begging us to cut out the middleman – it just needs a few companies who decide that they are going to be transparent and honest as part of their customer service strategy.

It just doesn't make sense to refer to humans as 'the most advanced AI'. That defies the very meaning of the term.

You're right that it's a game: this problem is entirely social, and because of that, I don't think it will end, however smart the tools get. You can think of it as the problem of building a model of what a 'good' dishwasher result is.

The modeling tools for forgery get smart just as quickly as the tools for detection – they're the same problems! If the answer to that is, “We should just let Google have all the good tools”… well, that's not going to happen.

Where this is going, of course, is that eventually fake dishwasher review sites will be composed of coherent English dishwasher reviews that are indistinguishable from real reviews in every possible way. Except that they're fake.

The problem is social; it's that there's someone out there who is willing to lie and deceive us to make a buck.

But that's a *really* hard problem to solve, so I guess we're left with technical band-aids that will, eventually, peel off.

Big hint: most of the blog posts are written by “admin”.

He showed MSFT and Google search results and curated search results in a blind ABC testing. And all investors said, C (curated) was best.

Sure, this can be done only with the most popular searches, 3-5 million!? You can't scale curation like stacking up CPUs.

And on a side note, reading @jonathanmendez mentioning Amazon, yes, Amazon is looking at its user data too, thus coming up with recommendations.

The main problem I see here is the use of simple keywords by Google, instead of decomposing words in context. Which requires learning if one does it right.

demo: http://www.jessops.com/ – click camera selector from horizontal menu.

But doing so highlights something I've been thinking about since I posted this and I'm somewhat surprised no one brought up: What would be a good search result for “dishwasher reviews”? I'm not sure I can find a site that should have come up. Which makes me wonder: is it a problem with search, or with the content out there on the web for certain topics like this?

The problem is that any system can be gamed. Google will change the rules and black hat SEOs will reverse engineer them and build new sites that exploit the new rules.

As Google keeps its secret sauce recipe to it self for all the reasons, we can only speculate who much brain power is behind PageRank, and how big or small are the timeframe from wave to wave of White and Black Hat SEO guys to get sites higher.

Kind of waves onto the beach, the the SEO guys want to see as much crap as possible stranding onto the beach.

This game will never end as long as we have no considerable computing power so that Google detects patterns very early in its beginning and is seeing the big picture of traffic (say Google DNS, Web history) on the network and our behavior.

We as humans are the most advances AI, so to speak, which detects fraud. You (Chris) detected very early reading that blog about dishwashers, that it was wonky and fraud, thus leaving the site very early. Now, this can Google read (maybe) in the future (say Google Chrome, ChromeOS, Google Open DNS) and feed back this into its alert system and eventually kicking the links from the blog out of its page rank.

Learning from our behavior is the greatest resource and mission asset Google has to pursue in its goal to collect all the worlds information and make it searchable. Thus ranking search results to our personal preference, location, time, search history, how educated you are, how old you are and so forth. All these levers make for a better search experience.

We somehow depend on Google to sift though the abundance of information (what a great business Google has, it found a need and created a need for accuracy).

And Google depends on us (balancing privacy concerns) to learn from us and feed it back into the algorithm and teaching its computers.

This comment could have been easily a short post.

Basically it takes a list of features that you determine are most important to your shopping criteria. Then slide some bars for priority and whala you have a list of products that fall into your “feature hot spot”.

Go look up customer reviews to make sure there are no glaring holes and pick one up.

Great post.

On a different note, I actually like consumersearch.com as a site. They provide a good summary of other sites' reviews, which save me a lot of time as a consumer to research and compare.

As far as the social graph for these sorts of thing goes, I think it's more about your social graph ranking/rating results…ie. Show me the 'dishwasher reviews' results that my social graph has ranked highest first (if there are any of course)…

Adding a human element (much like Hunch does by the way) is probably key to ensuring some level of quality and authenticity…

again just my humble opinion though