human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "from what to how an initial review of publicly available ai ethics tools methods and research to translate principles into practices"):
  Abstract: The debate about the ethical implications of Artificial Intelligence dates from the 1960s. However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such debate has primarily focused on principles - the what of AI ethics - rather than on practices, the how. Awareness of the potential issues is increasing at a fast rate, but the AI community's ability to take action to mitigate the associated risks is still at its infancy. Therefore, our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs.

Includes members:
  Member "ethically aligned design of autonomous systems industry viewpoint and an empirical study":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ai ethics in industry a research framework")
  Member "model cards for model reporting":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "explainability fact sheets a framework for systematic assessment of explainable approaches")
  Member "the ethics of ai ethics an evaluation of guidelines":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ethics of food recommender applications")
  Member "the global landscape of ai ethics guidelines":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ai safety state of the field through quantitative lens")
  Member "it s reducing a human being to a percentage perceptions of justice in algorithmic decisions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "questioning the assumptions behind fairness solutions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "pots protective optimization technologies")
  Member "enslaving the algorithm from a right to an explanation to a right to better decisions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "lifting interpretability performance trade off via automated feature engineering")
  Member "manipulating and measuring model interpretability":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CY(Computers and Society)