Power Dynamics
power dynamics
Exploring the neural landscape of imagination and abstract spaces
External cues imbued with significance can enhance the motivational state of an organism, trigger related memories and influence future planning and goal directed behavior. At the same time, internal thought and imaginings can moderate and counteract the impact of external motivational cues. The neural underpinnings of imagination have been largely opaque, due to the inherent inaccessibility of mental actions. The talk will describe studies utilizing imagination and tracking how its neural correlates bidirectionally interact with external motivational cues. Stimulus-response associative learning is only one form of memory organization. A more comprehensive and efficient organizational principal is the cognitive map. In the last part of the talk we will examine this concept in the case of abstract memories and social space. Social encounters provide opportunities to become intimate or estranged from others and to gain or lose power over them. The locations of others on the axes of power and affiliation can serve as reference points for our own position in the social space. Research is beginning to uncover the spatial-like neural representation of these social coordinates. We will discuss recent and growing evidence on utilizing the principals of the cognitive map across multiple domains, providing a systematic way of organizing memories to navigate life.
Protecting Machines from Us
The possibilities of machine learning and neural networks in particular are ever expanding. With increased opportunities to do good, however there are just as many opportunities to do harm and even in the case that good intentions are at the helm, evidence suggests that opportunities for good may eventually prove to be the opposite. The greatest threat to what machine learning is able to achieve and to us as humans, is machine learning that does not reflect the diversity of the users it is meant to serve. It is important that we are not so pre-occupied with advancing technology into the future that we have not taken the time to invest the energy into engineering the security measures this future requires. It is important to investigate now, as thoroughly as we investigate differing deep neural network architectures, the complex questions regarding the fact that humans and the society in which they operate is inherently biased and loaded with prejudice and that these traits find themselves in the machines we create (and increasingly allow to run our lives).