No abstract

No abstract

Artificial intelligence is becoming seamlessly integrated into our everyday lives, augmenting our knowledge and capabilities in driving, avoiding traffic, finding friends, choosing the perfect movie, and even cooking a healthier meal. It also has a significant impact on many aspects of society and industry, ranging from scientific discovery, healthcare and medical diagnostics to smart cities, transport and sustainability. Within this 21st century 'man meets machine' reality unfolding, several social and juristic challenges emerge for which we are poorly prepared. We here review social dilemmas where individual interests are at odds with the interests of others, and where artificial intelligence might have a particularly hard time making the right decision. An example thereof is the well-known social dilemma of autonomous vehicles. We also review juristic challenges, with a focus on torts that are at least partly or seemingly due to artificial intelligence, resulting in the claimant suffering a loss or harm. Here the challenge is to determine who is legally liable, and to what extent. We conclude with an outlook and with a short set of guidelines for constructively mitigating described challenges.

We study the effects of electrical and chemical autapse on the temporal coherence or firing regularity of single stochastic Hodgkin-Huxley neurons and scale-free neuronal networks. Also, we study the effects of chemical autapse on the occurrence of spatial synchronization in scale-free neuronal networks. Irrespective of the type of autapse, we observe autaptic time delay induced multiple coherence resonance for appropriately tuned autaptic conductance levels in single neurons. More precisely, we show that in the presence of an electrical autapse, there is an optimal intensity of channel noise inducing the multiple coherence resonance, whereas in the presence of chemical autapse the occurrence of multiple coherence resonance is less sensitive to the channel noise intensity. At the network level, we find autaptic time delay induced multiple coherence resonance and synchronization transitions, occurring at approximately the same delay lengths. We show that these two phenomena can arise only at a specific range of the coupling strength, and that they can be observed independently of the average degree of the network.

School tracking has been introduced as a means to provide skills the labor market demands, and as such has been in place for several decades in most Organisation for Economic Cooperation and Development (OECD) countries. The time is thus ripe for a critical review of the effects this has had on the equalities in education and opportunities later in life, and on the quality of vocational education in general. A synthesis of the existing literature reveals gaping holes between the dreams of superior vocational education and training that educational tracking ought to deliver, and the realities of lost opportunities and facilitated inequalities, especially in students with poor socioeconomic background, weak social capital, and sparse social networks. This is all the more true the sooner educational tracking comes into effect. While most OECD countries will start tracking students aged 15 or 16, some countries, such as Germany, will start doing this as early as age 10. Our review shows that this can have catastrophic consequences for students that for various reasons perform poorly early on, as they are indeed unable to recover due to the Matthew effect and preferential attachment in social networks, both of which punish false starts in life and reward first movers. To remedy the situation, we propose educational tracking be held off until later in life, and even then be undertaken with flexibility and late bloomers in mind. We also propose to restructure vocational education by decreasing the degree of curriculum differentiation, by allowing broader vocational education curricula, and by decreasing the number of training occupations in order to account for the changing labor market dynamics.

No abstract

We investigate the regularity of spontaneous spiking activity on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise and fraction of blocked voltage-gated sodium and potassium ion channels embedded in neuronal membranes. We show that there exists an optimal fraction of shortcut links between physically distant neurons, as well as an optimal intensity of intrinsic noise, which warrant an optimally ordered spontaneous spiking activity. This doubly coherence resonance-like phenomenon depends significantly, and can be controlled via the fraction of closed sodium and potassium ion channels, whereby the impacts can be understood via the analysis of the firing rate function as well as the deterministic system dynamics. Potential biological implications of our findings for information propagation across neural networks are also discussed.

No abstract