Forecasters using flexible neural networks (NN) in multi-horizon distributional regression setups often struggle to gain detailed insights into the underlying mechanisms that lead to the predicted feature-conditioned distribution parameters. In this work, we deploy a Neural Basis Model for Location, Scale and Shape, that blends the principled interpretability of GAMLSS with a computationally scalable shared basis decomposition, combined by linear projections supporting dedicated stepwise and parameter-wise feature shape functions aggregations. Experiments have been conducted on multiple market regions, achieving probabilistic forecasting performance comparable to that of distributional neural networks, while providing more insights into the model behavior through the learned nonlinear feature level maps to the distribution parameters across the prediction steps. Introduction Probabilistic forecasting of hourly electricity prices in day-ahead power markets (PEPF) is a complex problem with a significant impact. These enable informed decision-making in high-stakes scenarios such as trading strategies, resource scheduling, and optimal commitment by factoring in potential fluctuations and associated risks [2]. Moreover, electricity prices are characterized by high volatility and rapid changes driven by intricate factors, including distributed power demand, generation costs, and weather conditions [3].

This March, nearly 35,000 AI researchers, technologists, entrepreneurs, and concerned citizens signed an open letter from the nonprofit Future of Life Institute that called for a "pause" on AI development, due to the risks to humanity revealed in the capabilities of programs such as ChatGPT. "Contemporary AI systems are now becoming human-competitive at general tasks, and we must ask ourselves ... Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us?" I could still be proven wrong, but almost six months later and with AI development faster than ever, civilization hasn't crumbled. Heck, Bing Chat, Microsoft's "revolutionary," ChatGPT-infused search oracle, hasn't even displaced Google as the leader in search. So what should we make of the letter and similar sci-fi warnings backed by worthy names about the risks posed by AI? Two enterprising students at MIT, Isabella Struckman and Sofie Kupiec, reached out to the first hundred signatories of the letter calling for a pause on AI development to learn more about their motivations and concerns.