Philosophical Challenges PDF

Third paper: December 9 Final exam: December 9 or 18 Beliefs and Technology Beliefs and Technology “Inga hears from a friend that there is an art exhibition at the Museum of Modern Art in New York. Inga likes the idea of going, so she thinks about where the museum is, remembers it is on 53rd Str...

Third paper: December 9 Final exam: December 9 or 18 Beliefs and Technology Beliefs and Technology “Inga hears from a friend that there is an art exhibition at the Museum of Modern Art in New York. Inga likes the idea of going, so she thinks about where the museum is, remembers it is on 53rd Street, and sets off towards the museum.” Inga believes that the museum is on 53rd street because that information is in her memory. Clark and Chalmers 1998 Beliefs and Technology “Otto has Alzheimer’s. Since being diagnosed, Otto has developed an ingenious system to help him remember important things, structure his life, and navigate the world. Otto simply writes down what he needs to remember in a notebook which he carries around with him everywhere he goes. When he learns something he thinks will be important, he writes it in the notebook. When he needs to remember things, he searches his notebook for the information. Like Inga, Otto also hears about the exhibition at the museum. Having decided he’d like to go, Otto opens his notebook, finds the address for the museum, and heads off towards 53rd street.” Clark and Chalmers 1998 Beliefs and Technology Is there a principled reason for saying that Inga, but not Otto, believes that MOMA is on 53rd Street? 1. Both need to search for the information 2. Both have reliable access to the information 3. Both can lose access to the information Conclusion: Otto believes that the museum is on 53rd street because that information is in his notebook. Clark and Chalmers 1998 Beliefs and Technology Suppose that conclusion is right. 1. Can we store beliefs in our phones? 2. Can we store beliefs in other people? 3. Can we store beliefs in the internet? Clark and Chalmers 1998 Philosophical Challenges Computer Analogy The mind is like a computer Understanding Understanding 1. A computer doesn’t understand its inputs. 2. We understand our inputs. 3. Therefore, we are not computers. Understanding 1. The man in the Chinese room correctly manipulates symbols. 2. The man in the Chinese room does not understand Chinese. 3. Therefore, correctly manipulating symbols is not sufficient for understanding Chinese. 4. Computers are just devices for manipulating symbols. 5. Therefore, computers do not understand. Understanding Some responses: 1. The man doesn’t understand, but the “system” does. 2. The man doesn’t understand because he doesn’t perceive or act. 3. The system doesn’t understand because the symbol manipulations are too simple. 4. Understanding requires symbol manipulation in a biological mechanism Consciousness Consciousness 1. A computer isn’t necessarily conscious. 2. We are conscious. 3. Therefore, we are not merely computers. Free Will Free Will 1. A computer’s decisions are never free. 2. Our decisions are sometimes free. 3. Therefore, we are not computers. Creativity Creativity 1. A computer is never creative. 2. We are creative. 3. Therefore, we are not computers. Photorealistic Popeye Dall-E Chicken made of fried chicken Dall-E Rewrite Bohemian Rhapsody to be about the life of a postdoc ChatGPT ChatGPT Dynamic Systems Theory Dynamical Systems Theory 1. Dynamical systems are not computers. 2. We are dynamical systems. 3. Therefore, we are not computers. Dynamic Systems theory Dynamic Systems theory Dynamic Systems theory Dynamical Systems Theory Computational Description of the Watt Governor 1. Measure the speed of the flywheel. 2. Compare the actual speed against the desired speed. 3. If there is no discrepancy, return to step 1. Otherwise, a. measure the current steam pressure; b. calculate the desired alteration in steam pressure; c. calculate the necessary throttle valve adjustment. 4. Make the throttle valve adjustment. 5. Return to step 1. Dynamical Systems Theory Churchland et al. 2012 Dynamic Systems Theory Long-term memory with lots of information Dynamic Systems Theory Scrub jays remember: Where they buried food What they buried When they buried it Whether it’s still edible Long-term memory that searchable Dynamic Systems Theory Long-term memory with unpredictable delay Dynamic Systems Theory Multiple Sources of Evidence Dynamic Systems Theory Multiple Sources of Evidence Dynamic Systems Theory Adapting to a Fast-Changing Environment Dynamic Systems Theory Hypothesis Formation and Testing Dynamic Systems Theory Abstract Thoughts Neural Networks  The Classical Approach in Cognitive Science Neural Networks 65 * 32 0 Memory: 0 → 1 Neural Networks Neural Networks node 1 node 2 node 3 node 4 2x+1 and 2(X+1) are different algorithms with the same inputs and outputs. node 1 -0.50 0.23 0.34 -0.19 node 2 -0.15 0.23 -0.47 -0.39 I trained a network on these inputs and outputs. node 3 -0.44 -0.47 -0.31 0.26 Here are the weights that emerged between its first and second layer node 4 0.59 -0.32 0.53 -0.46 node 5 -0.64 0.22 -0.22 0.30 Which rule did it learn? node 6 0.66 0.10 -0.39 -0.40 node 7 -0.45 -0.49 0.25 0.18 It’s unclear!! node 8 0.56 0.34 -0.29 -0.45 Neural Networks Churchland: Neural Networks don’t use algorithms Dennet: If it’s helpful on a given occasion, we can choose to interpret a neural networks as using an algorithm Morrison: Neural Networks use algorithms, but we shouldn’t look for parts corresponding to each step