<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>bentcorner</author><text>I feel like you could enable FSD for every Tesla car in a &amp;quot;backseat driver&amp;quot; mode and have it mirror actions the driver does (so it doesn&amp;#x27;t have control but you&amp;#x27;re running it to see what it &lt;i&gt;would&lt;/i&gt; do, without acting on it), and you watch for any significant diversions.  Any time FSD wanted to do something but the driver did something else could have been a real disengagement.</text><parent_chain><item><author>ff317</author><text>The counterpoint goes something like this (not that I necessarily buy it, but this is what I infer to be Tesla&amp;#x27;s reasoning):&lt;p&gt;1) We&amp;#x27;re only going to fully &amp;quot;solve&amp;quot; self-driving with ML techniques to train deployed NNs; it can&amp;#x27;t be done purely in human-written deterministic code because the task is too complex.&lt;p&gt;2) Those NNs are only going to come up to the necessary levels of quality with a &lt;i&gt;ton&lt;/i&gt; of very-real-world test miles.  Various forms of &amp;quot;artificial&amp;quot; in-house testing and simulation can help in some ways, but without the real-world data you won&amp;#x27;t get anywhere.&lt;p&gt;3) Deploying cars into the real world (to gather the above) without some kind of safety driver doesn&amp;#x27;t seem like a great path either.  There&amp;#x27;s no backup driver to take over and intervene &amp;#x2F; unstick the car, and so far driverless taxi fleet efforts have been fairly narrowly geofenced for safety, which decreases the scope of scenarios they even get data on vs the whole real-world driving experience.&lt;p&gt;4) Therefore, the best plan to acquire the data to train the networks is to use a ton of customers as safety drivers and let them test it widely on the real routes they drive.  This is tricky and dangerous, but if it&amp;#x27;s not too dangerous and the outcome saves many lives over the coming years, it was worth it.</text></item><item><author>ivraatiems</author><text>I want to understand the minds of engineers at Tesla - or anywhere - who willingly put this kind of stuff out into the world. How do you convince yourself Tesla FSD is safe enough to ship? Are you just so worried about your boss being mad at you that you don&amp;#x27;t care? Are you so bought-in that you ignore obvious signs what you&amp;#x27;re doing is dangerous?&lt;p&gt;It&amp;#x27;s engineering malpractice to test this product on public roads, in my view. It&amp;#x27;s beyond malpractice that the government - at city, state, and federal levels - is allowing it.&lt;p&gt;(To be clear, I am not against self-driving cars in all instances. I am talking specifically about the Tesla FSD, which has been dangerous since launch and isn&amp;#x27;t getting better.)</text></item></parent_chain></comment><story><title>Tesla FSD data is getting worse, according to beta tester self-reports</title><url>https://electrek.co/2022/12/14/tesla-full-self-driving-data-awful-challenge-elon-musk-prove-otherwise/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>uvdn7</author><text>By this reasoning, shouldn&amp;#x27;t Tesla pay users instead to enable FSD and collect data for them?</text><parent_chain><item><author>ff317</author><text>The counterpoint goes something like this (not that I necessarily buy it, but this is what I infer to be Tesla&amp;#x27;s reasoning):&lt;p&gt;1) We&amp;#x27;re only going to fully &amp;quot;solve&amp;quot; self-driving with ML techniques to train deployed NNs; it can&amp;#x27;t be done purely in human-written deterministic code because the task is too complex.&lt;p&gt;2) Those NNs are only going to come up to the necessary levels of quality with a &lt;i&gt;ton&lt;/i&gt; of very-real-world test miles.  Various forms of &amp;quot;artificial&amp;quot; in-house testing and simulation can help in some ways, but without the real-world data you won&amp;#x27;t get anywhere.&lt;p&gt;3) Deploying cars into the real world (to gather the above) without some kind of safety driver doesn&amp;#x27;t seem like a great path either.  There&amp;#x27;s no backup driver to take over and intervene &amp;#x2F; unstick the car, and so far driverless taxi fleet efforts have been fairly narrowly geofenced for safety, which decreases the scope of scenarios they even get data on vs the whole real-world driving experience.&lt;p&gt;4) Therefore, the best plan to acquire the data to train the networks is to use a ton of customers as safety drivers and let them test it widely on the real routes they drive.  This is tricky and dangerous, but if it&amp;#x27;s not too dangerous and the outcome saves many lives over the coming years, it was worth it.</text></item><item><author>ivraatiems</author><text>I want to understand the minds of engineers at Tesla - or anywhere - who willingly put this kind of stuff out into the world. How do you convince yourself Tesla FSD is safe enough to ship? Are you just so worried about your boss being mad at you that you don&amp;#x27;t care? Are you so bought-in that you ignore obvious signs what you&amp;#x27;re doing is dangerous?&lt;p&gt;It&amp;#x27;s engineering malpractice to test this product on public roads, in my view. It&amp;#x27;s beyond malpractice that the government - at city, state, and federal levels - is allowing it.&lt;p&gt;(To be clear, I am not against self-driving cars in all instances. I am talking specifically about the Tesla FSD, which has been dangerous since launch and isn&amp;#x27;t getting better.)</text></item></parent_chain></comment><story><title>Tesla FSD data is getting worse, according to beta tester self-reports</title><url>https://electrek.co/2022/12/14/tesla-full-self-driving-data-awful-challenge-elon-musk-prove-otherwise/</url></story>