human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "society in the loop programming the algorithmic social contract"
  Abstract: Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, `SITL = HITL + Social Contract.'

Connected through hyperedge HE-1 (induced by source paper "factors influencing perceived fairness in algorithmic decision making algorithm outcomes development procedures and individual differences"):
  with members:
    - "mathematical notions vs human perception of fairness a descriptive approach to fairness for machine learning"
    - "improving fairness in machine learning systems what do industry practitioners need"
    - "the frontiers of fairness in machine learning"
    - "manipulating and measuring model interpretability"
    - "fairness and accountability design needs for algorithmic support in high stakes public sector decision making"
    - "a reductions approach to fair classification"
    - "demographics and discussion influence views on algorithmic fairness"
    - "network dissection quantifying interpretability of deep visual representations"

Connected through hyperedge HE-2 (induced by source paper "explaining the punishment gap of ai and robots"):
  with members:
    - "mind in the machine perceived minds induce decision change"

Connected through hyperedge HE-3 (induced by source paper "achieving ethical algorithmic behaviour in the internet of things a review"):
  with members:
    - "clarifying trust in social internet of things"
    - "building ethics into artificial intelligence"
    - "on a formal model of safe and scalable self driving cars"
    - "cyber physical systems security a survey"
    - "cognitive internet of things a new paradigm beyond connection"

Connected through hyperedge HE-4 (induced by source paper "dynamic algorithmic service agreements perspective"):
  with members:
    - "human self determination within algorithmic sociotechnical systems"
    - "model cards for model reporting"
    - "the role of cooperation in responsible ai development"
    - "datasheets for datasets"

Connected through hyperedge HE-5 (induced by source paper "ethics of technology needs more political philosophy"):
  with members:
    - "the social dilemma of autonomous vehicles"

Connected through hyperedge HE-6 (induced by source paper "towards governing agent s efficacy action conditional beta vae for deep transparent reinforcement learning"):
  with members:
    - "visual interpretability for deep learning a survey"
    - "world models"
    - "self consistent trajectory autoencoder hierarchical reinforcement learning with trajectory embeddings"
    - "independently controllable factors"
    - "scalable trust region method for deep reinforcement learning using kronecker factored approximation"
    - "stochastic variational video prediction"
    - "explaining how a deep neural network trained with end to end learning steers a car"
    - "visualizing and understanding atari agents"

Connected through hyperedge HE-7 (induced by source paper "the key concepts of ethics of artificial intelligence"):
  with members:
    - "towards moral autonomous systems"
    - "mammalian value systems"

Question: Please tell me which class the center node 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)