this post was submitted on 21 Aug 2023
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I'm definitely a fan of better enforcement of traffic rules to improve safety, but using ML* systems here is fraught with issues. ML systems tend to learn the human biases that were present in their training data and continue to perpetuate them. I wouldn't be shocked if these traffic systems, for example, disproportionately impact some racial groups. And if the ML system identifies those groups more frequently, even if the human review were unbiased (unlikely), the outcome would still be biased.
It's important to see good data showing these systems are fair, before they are used in the wild. I wouldn't support a system doing this until I was confident it was unbiased.
I think the lack of transparency about data, both the one used for training, and the actual statistics of the model itself is pretty worrying.
There needs to be regulations around that, because you can’t expect companies to automatically be transparent and forthcoming if they have something to gain by not being so.
This is a really important concern, thanks for bringing it up. I'd really like to know more about what they are doing in this case to try and combat that. Law enforcement in particular feels like an application where managing bias is extremely important.
I would imagine the risk of bias here is much lower than, for example, the predictive policing systems that are already in use in US police departments. Or the bias involved in ML models for making credit decisions. 🙃
Machine learning is a type of artificial intelligence. As is a pathfinding algorithm in a game.
Neural networks were some of the original AI systems dating back decades. Machine learning is a relatively new term for it.
AI is an umbrella term for anything that mimics intelligence.
There's nothing intelligent about it. It's no smarter than a chatbot or a phone's autocorrect. It's a buzzword applied to it by tech bros that want to make a bunch of money off it
Indeed. That's why it's called artificial intelligence.
Anything that attempts to mimic intelligence is AI.
The field was established in the 50s.
Your definition of it is wrong I'm afraid.
The only people that call it that are people who don't get what AI actually is or don't want to know because they think it's the future. There is exactly nothing intelligent about it. Stop spreading tech bro bullshit, call it machine learning bc that's what it actually is. Or are you really drinking the ML kool-aid hard enough that this is your hill to die on? It's not even as intelligent as a parrot that's learned to recognize colors and materials, it's literally just a souped up cleverbot
Literally the definition my friend. You just don't know what the term is refering to.
Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of human beings or animals. AI applications include advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon, and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or creative tools (ChatGPT and AI art), and competing at the highest level in strategic games (such as chess and Go).[1]
Artificial intelligence was founded as an academic discipline in 1956.[2] The field went through multiple cycles of optimism[3][4] followed by disappointment and loss of funding,[5][6] but after 2012, when deep learning surpassed all previous AI techniques,[7] there was a vast increase in funding and interest.
The various sub-fields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception, and support for robotics.[a] General intelligence (the ability to solve an arbitrary problem) is among the field's long-term goals.[8] To solve these problems, AI researchers have adapted and integrated a wide range of problem-solving techniques, including search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, probability, and economics.[b] AI also draws upon psychology, linguistics, philosophy, neuroscience and many other fields.[9]
I know exactly what AI is referring to. It's referring to a process that has no intelligence behind it. There is no "field of AI" it's a blatant misnomer, just like when they came up with "hoverboards" that still had wheels. Stop being a tech bro before you embarrass yourself and brag about your bored apes or some shit
Lol ok mate