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 "harnessing explanations to bridge ai and humans"):
  Abstract: Machine learning models are increasingly integrated into societally critical applications such as recidivism prediction and medical diagnosis, thanks to their superior predictive power. In these applications, however, full automation is often not desired due to ethical and legal concerns. The research community has thus ventured into developing interpretable methods that explain machine predictions. While these explanations are meant to assist humans in understanding machine predictions and thereby allowing humans to make better decisions, this hypothesis is not supported in many recent studies. To improve human decision-making with AI assistance, we propose future directions for closing the gap between the efficacy of explanations and improvement in human performance.

Includes members:
  Member "why is chicago deceptive towards building model driven tutorials for humans":
    also connected through other hyperedges:
      (none)
  Member "an evaluation of the human interpretability of explanation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "auditing and debugging deep learning models via decision boundaries individual level and group level analysis")
  Member "on human predictions with explanations and predictions of machine learning models a case study on deception detection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "learning the difference that makes a difference with counterfactually augmented data":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "beat the ai investigating adversarial human annotations for reading comprehension")
  Member "manipulating and measuring model interpretability":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "rationalizing neural predictions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "description based text classification with reinforcement learning")
  Member "why should i trust you explaining the predictions of any classifier":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "secure and robust machine learning for healthcare a survey")

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.HC(Human-Computer Interaction)