Showing posts with the label biology

How Much Do Wild Animals Suffer? A Foundational Result on the Question is Wrong.

In 1995, Yew-Kwang Ng wrote a groundbreaking paper, "Towards welfare biology: Evolutionary economics of animal consciousness and suffering" that explored the novel question of the wellbeing of wild animals as distinct from the conservation of species. As perceptive as it was innovative, the paper proposed a number of axioms about evolution and consciousness to study which animals are sentient, what their experiences are, and what might be done about it.

Among the many results in the paper was the Buddhist Premise, which stated that under reasonable conditions, suffering should exceed enjoyment for the average wild animal. The finding matches the intuitions of many people who have thought about the issue and concluded that nature is "red in tooth and claw" in Alfred, Lord Tennyson's phrase. As it turns out, though, this "evolutionary economics" argument is wrong. This week, Ng and I published a new paper showing that the original "Buddhist Premise&…

Is a Computer Neuron the Same as a Brain Neuron?

When I took a philosophy of mind class in high school, my professor proposed neural networks in computer science as a potential way to create consciousness. At the very least, it's a way to create high levels of intelligence. I didn't know exactly what a computerized neural network consisted of (I imagined it being built in hardware), and I still don't, really, but I'm curious: how similar is an artificial neural network to a biological one? Is it really a good replication?

From an article on the similarities and differences

An [Artificial Neural Network] consists of layers made up of interconnected neurons that receive a set of inputs and a set of weights. It then does some mathematical manipulation and outputs the results as a set of “activations” that are similar to synapses in biological neurons. While ANNs typically consist of hundreds to maybe thousands of neurons, the biological neural network of the human brain consists of billions.
On the other hand: