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Artificial intelligence (AI) ethics has emerged as a burgeoning yet pivotal area of scholarly research. This study conducts a comprehensive bibliometric analysis of the AI ethics literature over the past two decades. The analysis reveals a discernible tripartite progression, characterized by an incubation phase, followed by a subsequent phase focused on imbuing AI with human-like attributes, culminating in a third phase emphasizing the development of human-centric AI systems. After that, they present seven key AI ethics issues, encompassing the Collingridge dilemma, the AI status debate, challenges associated with AI transparency and explainability, privacy protection complications, considerations of justice and fairness, concerns about algocracy and human enfeeblement, and the issue of superintelligence. Finally, they identify two notable research gaps in AI ethics regarding the large ethics model (LEM) and AI identification and extend an invitation for further scholarly research.

As is well known, using piecewise linear polynomial collocation (PLC) and piecewise quadratic polynomial collocation (PQC), respectively, to approximate the weakly singular integral $$I(a,b,x) =\int^b_a \frac{u(y)}{|x-y|^\gamma}dy, \quad x \in (a,b) ,\quad 0< \gamma <1,$$ have the local truncation error $\mathcal{O}\left(h^2\right)$ and $\mathcal{O}\left(h^{4-\gamma}\right)$. Moreover, for Fredholm weakly singular integral equations of the second kind, i.e., $\lambda u(x)- I(a,b,x) =f(x)$ with $ \lambda \neq 0$, also have global convergence rate $\mathcal{O}\left(h^2\right)$ and $\mathcal{O}\left(h^{4-\gamma}\right)$ in [Atkinson and Han, Theoretical Numerical Analysis, Springer, 2009]. Formally, following nonlocal models can be viewed as Fredholm weakly singular integral equations $$\int^b_a \frac{u(x)-u(y)}{|x-y|^\gamma}dy =f(x), \quad x \in (a,b) ,\quad 0< \gamma <1.$$ However, there are still some significant differences for the models in these two fields. In the first part of this paper we prove that the weakly singular integral by PQC have an optimal local truncation error $\mathcal{O}\left(h^4\eta_i^{-\gamma}\right)$, where $\eta_i=\min\left\{x_i-a,b-x_i\right\}$ and $x_i$ coincides with an element junction point. Then a sharp global convergence estimate with $\mathcal{O}\left(h\right)$ and $\mathcal{O}\left(h^3\right)$ by PLC and PQC, respectively, are established for nonlocal problems. Finally, the numerical experiments including two-dimensional case are given to illustrate the effectiveness of the presented method., Comment: 24pages, 2 figures