373 Hits in 4.3 sec

Generative Adversarial Imitation Learning for Empathy-based AI [article]

Pratyush Muthukumar, Karishma Muthukumar, Deepan Muthirayan, Pramod Khargonekar
2021 arXiv   pre-print
In this paper, we utilize the GAIL model for text generation to develop empathy-based context-aware conversational AI.  ...  Generative adversarial imitation learning (GAIL) is a model-free algorithm that has been shown to provide strong results in imitating complex behaviors in high-dimensional environments.  ...  They propose the application of a generative adversarial imitation learning model for traditional text generation.  ... 
arXiv:2105.13328v1 fatcat:agbxrbl4rbhrhbz4zsgkll3w2q

From Identifying Dog Breeds to Diagnosing Diabetic Retinopathy

Shafaz Veettil, Logan Van Nynatten
2019 University of Western Ontario Medical Journal  
Limitations include an inability to wholly substitute for human empathy and touch, a vulnerability for adversarial training, and concerns about interpretability.  ...  Google and others are leveraging deep learning, a subset of AI that aims to imitate the neuronal processing of the human brain, to screen for diseases—such as diabetic retinopathy, cardiovascular disease  ...  AI-like a humanis vulnerable to adversarial training 2,10,21 ; if the dataset an AI is trained on is biased, then the output diagnosis produced by the AI will be biased.  ... 
doi:10.5206/uwomj.v87i2.1137 fatcat:vlkhzteoznevhcmrx2hpgkyln4

A New Hermeneutics of Suspicion? The Challenge of deepfakes to Theological Epistemology

Clifford Anderson
2019 Cursor_ Zeitschrift für explorative Theologie  
In this paper, I provide an introduction to deepfakes and related machine-learning technologies for theologians, considering their potential use and misuse in theology.  ...  As Christians, we learn that appearances can be deceiving, misleading, or at least obscure underlying reality.  ...  Ian Goodfellow, "NIPS 2016 Tutorial: Generative Adversarial Networks," December 2016, 34. ↩ . Tianxiang Shen et al., "'Deep Fakes' Using Generative Adversarial Networks (GAN)," 2018, 1. ↩ .  ... 
doi:10.21428/fb61f6aa.771d30b7 fatcat:dntiks2esngwphrrkhnjnuar4q

Ideas from Developmental Robotics and Embodied AI on the Questions of Ethics in Robots [article]

Alexandre Pitti
2018 arXiv   pre-print
of the body, recognition of the intention of others,predictive coding, active inference, the role of feedback and error, imitation, artificialcuriosity and contextual learning.  ...  We would like to highlight someprinciples and ideas from cognitive neuroscience and development sciences based on theimportance of the body for intelligence, contrary to the theory of the all-brain or  ...  like the generative adversarial networks (Goodfellows et al., 2014), or some implementations of predictive coding (Spratling, 2016) .  ... 
arXiv:1803.07506v1 fatcat:p4mua635rjgrlnrv6cpm2is4au

Artificial Empathy: A New Perspective for Analyzing and Designing Multi-agent Systems

Jize Chen, Dali Zhang, Zhenshen Qu, Changhong Wang
2020 IEEE Access  
Then we present a bandit algorithm called Empathy-based Interactive Learner (EIL), by which agents can enable affective utility evaluation and adaptive learning procedure in multi-agent systems.  ...  Learning from biological mechanisms is an essential method of devising interaction rules among agents.  ...  Then, to give a general application paradigm of artificial empathy, we will demonstrate an empathy-based learning method in bandit environments. A.  ... 
doi:10.1109/access.2020.3029502 fatcat:tl62nrrvovfovgvqdlqbk6t3j4

A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions

Ali Mohammad Saghiri, S. Mehdi Vahidipour, Mohammad Reza Jabbarpour, Mehdi Sookhak, Agostino Forestiero
2022 Applied Sciences  
In the near future, because of the use of AI-based generative data, such as generative adversarial networks (GANs), we would need some technology to differentiate real-world and appropriate data from other  ...  After the invention of some modes, such as generative adversarial networks (GANs) [39] , machines can generate data samples.  ... 
doi:10.3390/app12084054 fatcat:mqmhxiesrrcf3nrdoq653afafq

Text Analysis in Adversarial Settings: Does Deception Leave a Stylistic Trace? [article]

Tommi Gröndahl, N. Asokan
2019 arXiv   pre-print
Textual deception constitutes a major problem for online security.  ...  By conducting an extensive literature review of existing empirical work, we demonstrate that while certain linguistic features have been indicative of deception in certain corpora, they fail to generalize  ...  She y et al. [157] present a Generative Adversarial Network (GAN) -based approach to style transformation, which they title Adversarial Author A ribute Anonymity Neural Translation (A 4 NT).  ... 
arXiv:1902.08939v2 fatcat:qjbxcq5fpjaubj5z5xii3v44mu

A Roadmap for Big Model [article]

Sha Yuan, Hanyu Zhao, Shuai Zhao, Jiahong Leng, Yangxiao Liang, Xiaozhi Wang, Jifan Yu, Xin Lv, Zhou Shao, Jiaao He, Yankai Lin, Xu Han (+88 others)
2022 arXiv   pre-print
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.  ...  At the end of this paper, we conclude the further development of BMs in a more general view.  ...  Following works craft adversarial examples based on BERT itself [464, 463] or using generative models [963] .  ... 
arXiv:2203.14101v4 fatcat:rdikzudoezak5b36cf6hhne5u4

AI and Medicine [article]

Mihai Nadin
2019 arXiv   pre-print
Which part of medicine, if any, can and should be entrusted to AI, now or at some moment in the future? That both medicine and AI will continue to change goes without saying.  ...  Funding for the research on which this paper is based was provided by the antÈ-Institute for Research in Anticipatory Systems. Dr.  ...  Acknowledgments Many practicing physicians, to whom I wish to express gratitude for their tolerance of someone who questioned their profession, educated me without turning me into a practicing doctor.  ... 
arXiv:2001.00641v1 fatcat:jb7ou5b5nrh3fhjrgwzw7e5msi

Aligning AI With Shared Human Values [article]

Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt
2021 arXiv   pre-print
Our work shows that progress can be made on machine ethics today, and it provides a steppingstone toward AI that is aligned with human values.  ...  This requires connecting physical and social world knowledge to value judgements, a capability that may enable us to steer chatbot outputs or eventually regularize open-ended reinforcement learning agents  ...  Funding for the ETHICS dataset was generously provided by the Long-Term Future Fund. This research was also supported by the NSF Frontier Award 1804794.  ... 
arXiv:2008.02275v5 fatcat:dcq5jt2nibgedajzxsibnpf2xq

Text Analysis in Adversarial Settings

Tommi Gröndahl, N. Asokan
2019 ACM Computing Surveys  
Textual deception constitutes a major problem for online security.  ...  By conducting an extensive literature review of existing empirical work, we demonstrate that while certain linguistic features have been indicative of deception in certain corpora, they fail to generalize  ...  [82] outline a basic model of rule-based style imitation based on grammatical changes.  ... 
doi:10.1145/3310331 fatcat:563vjvd63fcdnnswmvmsxthu7e

India, The Fourth Industrial Revolution and Government Policy

S. Patanjali, D. Subramaniam
2019 Arthshastra Indian Journal of Economics & Research  
Artificial intelligence and machine learning capabilities are growing at an unprecedented rate.  ...  p.1 4 General Framework for AI & Security Threats : Increasingly realistic synthetic faces generated by variations on Generative Adversarial Networks (GANs).  ...  Indeed, some popular accounts of AI and cybersecurity include claims based on circumstantial evidence that AI is already being used for offense by sophisticated and motivated adversaries .  ... 
doi:10.17010/aijer/2019/v8i2/145224 fatcat:srchlppo6za4hd4klygunfpwuq

Socio-cognitive biases in folk AI ethics and risk discourse

Michael Laakasuo, Volo Herzon, Silva Perander, Marianna Drosinou, Jukka Sundvall, Jussi Palomäki, Aku Visala
2021 AI and Ethics  
AbstractThe ongoing conversation on AI ethics and politics is in full swing and has spread to the general public.  ...  The central claim is that much of our mostly opaque intuitive thinking has not evolved to match the nature of AI, and this causes problems in democratizing AI ethics and politics.  ...  Acknowledgements The authors would like to thank Jane and Aatos Erkko Foundation (grant number 170112) and the Academy of Finland (Grant number 323207) for their funding.  ... 
doi:10.1007/s43681-021-00060-5 fatcat:55h34xzvlveptal3qrp7ky536i

Conversational Agents: Goals, Technologies, Vision and Challenges

Merav Allouch, Amos Azaria, Rina Azoulay
2021 Sensors  
Capable of conducting ongoing communication with humans, CAs are encountered in natural-language processing, deep learning, and technologies that integrate emotional aspects.  ...  The technologies used for the evaluation of CAs and publicly available datasets are outlined.  ...  [145] developed Zhorai, a CA that enables children to explore AI algorithms and machine learning.  ... 
doi:10.3390/s21248448 pmid:34960538 pmcid:PMC8704682 fatcat:vhylbunhwbbhfa65bdqmnqpi5q

Can Computers Create Art? [article]

Aaron Hertzmann
2018 arXiv   pre-print
The current hype and reality of Artificial Intelligence (AI) tools for art making is then discussed, together with predictions about how AI tools will be used.  ...  In each case, there were initial fears and denial of the technology, followed by a blossoming of new creative and professional opportunities for artists.  ...  Thanks to Shira Katz, Alvy Ray Smith, Craig Kaplan, Shiry Ginosar, and Dani Oore for valuable comments on the manuscript.  ... 
arXiv:1801.04486v6 fatcat:mhocgimdx5b75novngkdcunjuq
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