125 research outputs found

    Six Human-Centered Artificial Intelligence Grand Challenges

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    Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are human-centered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human well-being, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human’s cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies

    What makes you not a Buddhist? : a preliminary mapping of values

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    This study sets out to establish which Buddhist values contrasted with or were shared by adolescents from a non-Buddhist population. A survey of attitude toward a variety of Buddhist values was fielded in a sample of 352 non-Buddhist schoolchildren aged between 13 and 15 in London. Buddhist values where attitudes were least positive concerned the worth of being a monk/nun or meditating, offering candles & incense on the Buddhist shrine, friendship on Sangha Day, avoiding drinking alcohol, seeing the world as empty or impermanent and Nirvana as the ultimate peace. Buddhist values most closely shared by non-Buddhists concerned the Law of Karma, calming the mind, respecting those deserving of respect, subjectivity of happiness, welfare work, looking after parents in old age and compassion to cuddly animals. Further significant differences of attitude toward Buddhism were found in partial correlations with the independent variables of sex, age and religious affiliation. Correlation patterns paralleled those previously described in theistic religions. Findings are applied to spiritual, moral, social and cultural development and for the teaching of religious to pupils of no faith adherence. The study recommends that quantitative psychometrics employed to conceptualize Buddhist values by discriminant validity in this study could be extended usefully to other aspects of the study of Buddhism, particularly in quest of validity in the conceptualization of Buddhist identity within specifically Buddhist populations

    Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

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    Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs

    Does inequality erode generalized trust? Evidence from Romanian youths

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    Generalized trust is a critical component of liberal democratic citizenship. We evaluate the extent to which exposure to socioeconomic inequality erodes trust among Romanian youths. Using national survey data of Romanian eighth-grade and high school students, we evaluate this effect as a product of socioeconomic diversity within the classroom, controlling for the social status of the students as well as socioeconomic inequality within the community where the school is located. Our analysis shows that generalized trust is higher for students in higher grades. However, despite this maturing effect, students exposed to greater levels of socioeconomic diversity have significantly lower levels of trust. The effect is particularly acute for students in the ninth grade. This finding holds when controlling for socioeconomic diversity and polarization in the community. The result reinforces the idea that generalized trust develops early in one’s life and is quite stable, although a major life transformation, such as entering high school, may alter trust depending on the social context

    Breaking cover: neural responses to slow and fast camouflage-breaking motion.

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    Primates need to detect and recognize camouflaged animals in natural environments. Camouflage-breaking movements are often the only visual cue available to accomplish this. Specifically, sudden movements are often detected before full recognition of the camouflaged animal is made, suggesting that initial processing of motion precedes the recognition of motion-defined contours or shapes. What are the neuronal mechanisms underlying this initial processing of camouflaged motion in the primate visual brain? We investigated this question using intrinsic-signal optical imaging of macaque V1, V2 and V4, along with computer simulations of the neural population responses. We found that camouflaged motion at low speed was processed as a direction signal by both direction- and orientation-selective neurons, whereas at high-speed camouflaged motion was encoded as a motion-streak signal primarily by orientation-selective neurons. No population responses were found to be invariant to the camouflage contours. These results suggest that the initial processing of camouflaged motion at low and high speeds is encoded as direction and motion-streak signals in primate early visual cortices. These processes are consistent with a spatio-temporal filter mechanism that provides for fast processing of motion signals, prior to full recognition of camouflage-breaking animals
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