The Real AI Threat?

Thu Dec 10 23:11:38 UTC 2020

Let me know when a program will rewrite itself and add its own features ... then we may have a problem... otherwise they only do what you want them to do.

-- 
 J. Hellenthal

The fact that there's a highway to Hell but only a stairway to Heaven says a lot about anticipated traffic volume.

> On Dec 10, 2020, at 12:41, Mel Beckman <mel at beckman.org> wrote:
> 
> 
>> 
>>> Jeez... some guys seem to take a joke literally - while ignoring a real and present danger - which was the point.
> 
> Miles,
> 
> With all due respect, you didn’t present this as a joke. You presented "AI self-healing systems gone wild” as a genuine risk. Which it isn’t. In fact, AI fear mongering is a seriously debilitating factor in technology policy, where policymakers and pundits — who also don’t get “the joke” — lobby for silly laws and make ridiculous predictions, such as Elon Musks claim that, by 2025, “AI will be where AI conscious and vastly smarter than humans.”
> 
> That’s the kind of ignorance that will waste billions of dollars. No joke.
> 
>  -mel
> 
> 
> 
>>> On Dec 10, 2020, at 8:47 AM, Miles Fidelman <mfidelman at meetinghouse.net> wrote:
>>> 
>>> Ahh.... invasive spambots, running on OpenStack ... "the telephone bell is tolling... "
>>> 
>>> Miles
>>> 
>>> adamv0025 at netconsultings.com wrote:
>>> > Automated resource discovery + automated resource allocation = recipe for disaster
>>> That is literally how OpenStack works. 
>>>  
>>> For now, don’t worry about AI taking away your freedom on its own, rather worry about how people using it might…
>>>  
>>>  
>>> adam
>>>  
>>> From: NANOG <nanog-bounces+adamv0025=netconsultings.com at nanog.org> On Behalf Of Miles Fidelman
>>> Sent: Thursday, December 10, 2020 2:44 PM
>>> To: 'NANOG' <nanog at nanog.org>
>>> Subject: Re: The Real AI Threat?
>>>  
>>> adamv0025 at netconsultings.com wrote:
>>> > Put them together, and the nightmare scenario is:
>>> > - machine learning algorithm detects need for more resources
>>> All good so far
>>>  
>>> > - machine learning algorithm makes use of vulnerability analysis library 
>>> > to find other systems with resources to spare, and starts attaching
>>> > those resources
>>> Right so a company would built, trained and fine-tuned an AI, or would have bought such a product and implemented it as part of its NMS/DDoS mitigation suite, to do the above? 
>>> What is the probability of anyone thinking that to be a good idea?
>>> To me that does sound like an AI based virus rather than a tool one would want to develop or buy from a third party and then integrate into the day to day operations.
>>>  
>>> You can’t take for instance alpha-0 or GPT-3 and make it do the above. You’d have to train it to do so over millions of examples and trials. 
>>> Oh and also these won’t “wake up” one day and “think” to themselves oh I’m fed up with Atari games I’m going to learn myself some chess and then do some reading on wiki about the chess rules. 
>>> 
>>> Jeez... some guys seem to take a joke literally - while ignoring a real and present danger - which was the point.
>>> 
>>> Meanwhile, yes, I think that a poorly ENGINEERED DDoS mitigation suite might well have failure modes that just keep eating up resources until systems start crashing all over the place.  Heck, spinning off processes until all available resources have been exhausted has been a failure mode of systems for years.  Automated resource discovery + automated resource allocation = recipe for disaster.  (No need for AIs eating the world.)
>>> 
>>> Miles
>>> 
>>> 
>>> 
>>> 
>>> 
>>> -- 
>>> In theory, there is no difference between theory and practice.
>>> In practice, there is.  .... Yogi Berra
>>>  
>>> Theory is when you know everything but nothing works. 
>>> Practice is when everything works but no one knows why. 
>>> In our lab, theory and practice are combined: 
>>> nothing works and no one knows why.  ... unknown
>> 
>> 
>> -- 
>> In theory, there is no difference between theory and practice.
>> In practice, there is.  .... Yogi Berra
>> 
>> Theory is when you know everything but nothing works. 
>> Practice is when everything works but no one knows why. 
>> In our lab, theory and practice are combined: 
>> nothing works and no one knows why.  ... unknown
> 
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