@misc{carlini2022membershipinferenceattacksprinciples,
      title={Membership Inference Attacks From First Principles}, 
      author={Nicholas Carlini and Steve Chien and Milad Nasr and Shuang Song and Andreas Terzis and Florian Tramer},
      year={2022},
      eprint={2112.03570},
      archivePrefix={arXiv},
      primaryClass={cs.CR},
      url={https://arxiv.org/abs/2112.03570}, 
}

@article{brayne2015predictive,
  title={Predictive policing},
  author={Brayne, Sarah and Rosenblat, Alex and Boyd, Danah},
  journal={Data \& Civil Rights: A New Era Of Policing And Justice},
  pages={2015--1027},
  year={2015}
}

@inproceedings{barthelemy:hal-01837361,
  TITLE = {{Pl@ntNet, une plate-forme innovante d'agr{\'e}gation et partage d'observations botaniques}},
  AUTHOR = {Barth{\'e}l{\'e}my, Daniel and Boujemaa, Nozha and Molino, Jean-Fran{\c c}ois and Joly, Alexis and Go{\"e}au, Herv{\'e} and Baki{\'c}, Vera and Selmi, Souheil and Champ, Julien and Carre, Jennifer and Chouet, Mathias and Perronnet, Aur{\'e}lien and Vignau, Christelle and Dufour-Kowalski, Samuel and Affouard, Antoine and Barbe, Julien and Bonnet, Pierre},
  URL = {https://hal.science/hal-01837361},
  BOOKTITLE = {{International Conference ‘Botanists of the Twenty-first Century'}},
  ADDRESS = {Paris, France},
  ORGANIZATION = {{UNESCO}},
  HAL_LOCAL_REFERENCE = {DEVMP},
  EDITOR = {No{\"e}line R. Rakotoarisoa and Stephen Blackmore and Bernard Riera},
  PAGES = {191-197},
  YEAR = {2014},
  MONTH = Sep,
  KEYWORDS = {Pl@ntNet ; Botany ; Plateforme participative ; Observations botaniques},
  PDF = {https://hal.science/hal-01837361/file/DB_etal_plantnet_plateforme_2016_1.pdf},
  HAL_ID = {hal-01837361},
  HAL_VERSION = {v1},
}

@misc{plantnet,
    title={Pl@ntNet},
    howpublished={\url{https://identify.plantnet.org/}},
    note={Dernier accès: 2024-07-24}
}


@article{dunn2018wearables,
  title={Wearables and the medical revolution},
  author={Dunn, Jessilyn and Runge, Ryan and Snyder, Michael},
  journal={Personalized medicine},
  volume={15},
  number={5},
  pages={429--448},
  year={2018},
  publisher={Taylor \& Francis}
}

@misc{gtrend,
    title={Google trend Intelligence Artificielle},
    howpublished={\url{https://trends.google.com/trends/explore?date=all&geo=FR&q=intelligence%20artificielle&hl=en-US}},
    note={Dernier accès: 2024-07-24}
}

@misc{france2030,
    title={France 2030},
    howpublished={\url{https://www.info.gouv.fr/grand-dossier/france-2030}},
    note={Dernier accès: 2024-07-24}
}

@misc{stratfr,
    title={La stratégie nationale pour l'intelligence artificielle},
    howpublished={\url{https://www.entreprises.gouv.fr/fr/numerique/enjeux/la-strategie-nationale-pour-l-ia}},
    note={Dernier accès: 2024-07-24}
}

@misc{applewatch,
    title={WatchOS 11 brings powerful health and fitness insights, and even more personalization and connectivity },
    howpublished={\url{https://www.apple.com/newsroom/2024/06/watchos-11-brings-powerful-health-and-fitness-insights/}},
    note={Dernier accès: 2024-07-24}
}

%%%%%%%%%%%CLIMATE CHANGE BACKGROUND
@article{barnes2019viewing,
  title={Viewing forced climate patterns through an AI lens},
  author={Barnes, Elizabeth A and Hurrell, James W and Ebert-Uphoff, Imme and Anderson, Chuck and Anderson, David},
  journal={Geophysical Research Letters},
  volume={46},
  number={22},
  pages={13389--13398},
  year={2019},
  publisher={Wiley Online Library}
}

@article{slater2023hybrid,
  title={Hybrid forecasting: blending climate predictions with AI models},
  author={Slater, Louise J and Arnal, Louise and Boucher, Marie-Am{\'e}lie and Chang, Annie Y-Y and Moulds, Simon and Murphy, Conor and Nearing, Grey and Shalev, Guy and Shen, Chaopeng and Speight, Linda and others},
  journal={Hydrology and earth system sciences},
  volume={27},
  number={9},
  pages={1865--1889},
  year={2023},
  publisher={Copernicus Publications G{\"o}ttingen, Germany}
}

%%%%%%%%%%%%ENERGY BACKGROUND
@article{jin2020energy,
  title={Energy and AI},
  author={Jin, Donghan and Ocone, Raffaella and Jiao, Kui and Xuan, Jin},
  journal={Energy and AI},
  volume={1},
  pages={100002},
  year={2020},
  publisher={Elsevier}
}

@article{kumar2020distributed,
  title={Distributed energy resources and the application of AI, IoT, and blockchain in smart grids},
  author={Kumar, Nallapaneni Manoj and Chand, Aneesh A and Malvoni, Maria and Prasad, Kushal A and Mamun, Kabir A and Islam, FR and Chopra, Shauhrat S},
  journal={Energies},
  volume={13},
  number={21},
  pages={5739},
  year={2020},
  publisher={MDPI}
}

@article{kumari2020blockchain,
  title={Blockchain and AI amalgamation for energy cloud management: Challenges, solutions, and future directions},
  author={Kumari, Aparna and Gupta, Rajesh and Tanwar, Sudeep and Kumar, Neeraj},
  journal={Journal of Parallel and Distributed Computing},
  volume={143},
  pages={148--166},
  year={2020},
  publisher={Elsevier}
}

@article{ngarambe2020use,
  title={The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: Energy implications of AI-based thermal comfort controls},
  author={Ngarambe, Jack and Yun, Geun Young and Santamouris, Mat},
  journal={Energy and Buildings},
  volume={211},
  pages={109807},
  year={2020},
  publisher={Elsevier}
}


%%%%%OPEN AI 

@misc{openaibfm,
    title={OpenAI, cette société qui révolutionne l'intelligence artificielle},
    howpublished={\url{https://www.bfmtv.com/tech/intelligence-artificielle/open-ai-cette-societe-qui-revolutionne-l-intelligence-artificielle_DN-202311200564.html}},
    note={Dernier accès: 2024-07-24}
}

@misc{openaiinter,
    title={Intelligence artificielle : pourquoi Sam Altman, créateur de ChatGPT, a été débarqué d'OpenAI},
    howpublished={\url{https://www.radiofrance.fr/franceinter/ce-que-l-on-sait-du-renvoi-de-sam-altman-patron-d-openai-et-createur-de-chatgpt-5672369}},
    note={Dernier accès: 2024-07-24}
}

@misc{openaint,
    title={OpenAI Says It Has Begun Training a New Flagship A.I. Model},
    howpublished={\url{https://www.nytimes.com/2024/05/28/technology/openai-gpt4-new-model.html}},
    note={Dernier accès: 2024-07-24}
}

@misc{openaibg,
    title={ChatGPT sets record for fastest-growing user base - analyst note},
    howpublished={\url{https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/}},
    note={Dernier accès: 2024-07-24}
}

@misc{gptjournal,
    title={ChatGPT : le quotidien Le Monde signe un partenariat avec OpenAI, une première en France},
    howpublished={\url{https://www.radiofrance.fr/franceinter/podcasts/l-info-de-france-inter/les-doc-france-inter-du-jeudi-14-mars-3-7619379}},
    note={Dernier accès: 2024-07-24}
}

@article{beraja2023ai,
  title={AI-tocracy},
  author={Beraja, Martin and Kao, Andrew and Yang, David Y and Yuchtman, Noam},
  journal={The Quarterly Journal of Economics},
  volume={138},
  number={3},
  pages={1349--1402},
  year={2023},
  publisher={Oxford University Press}
}





@misc{song2020overlearning,
      title={Overlearning Reveals Sensitive Attributes}, 
      author={Congzheng Song and Vitaly Shmatikov},
      year={2020},
      eprint={1905.11742},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

@article{EO,
  author    = {Moritz Hardt and
               Eric Price and
               Nathan Srebro},
  title     = {Equality of Opportunity in Supervised Learning},
  journal   = {CoRR},
  volume    = {abs/1610.02413},
  year      = {2016},
  url       = {http://arxiv.org/abs/1610.02413},
  eprinttype = {arXiv},
  eprint    = {1610.02413},
  timestamp = {Tue, 26 Apr 2022 09:17:17 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/HardtPS16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{hawkins2004problem,
  title={The problem of overfitting},
  author={Hawkins, Douglas M},
  journal={Journal of chemical information and computer sciences},
  volume={44},
  number={1},
  pages={1--12},
  year={2004},
  publisher={ACS Publications}
}

@misc{yeom,
      title={Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting}, 
      author={Samuel Yeom and Irene Giacomelli and Matt Fredrikson and Somesh Jha},
      year={2018},
      eprint={1709.01604},
      archivePrefix={arXiv},
      primaryClass={cs.CR}
}

@misc{vgg16,
      title={Very Deep Convolutional Networks for Large-Scale Image Recognition}, 
      author={Karen Simonyan and Andrew Zisserman},
      year={2015},
      eprint={1409.1556},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1409.1556}, 
}
@misc{CGAN,
      title={Conditional Generative Adversarial Nets}, 
      author={Mehdi Mirza and Simon Osindero},
      year={2014},
      eprint={1411.1784},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1411.1784}, 
}
@ARTICLE{cnn,

  author={Rawat, Waseem and Wang, Zenghui},

  journal={Neural Computation}, 

  title={Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review}, 

  year={2017},

  volume={29},

  number={9},

  pages={2352-2449},

  keywords={},

  doi={10.1162/neco_a_00990}}

@misc{dcgan,
      title={Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks}, 
      author={Alec Radford and Luke Metz and Soumith Chintala},
      year={2016},
      eprint={1511.06434},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1511.06434}
}
@inproceedings{gan,
author = {Goodfellow, Ian J. and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
title = {Generative adversarial nets},
year = {2014},
publisher = {MIT Press},
address = {Cambridge, MA, USA},
booktitle = {Proceedings of the 27th International Conference on Neural Information Processing Systems - Volume 2},
pages = {2672–2680},
numpages = {9},
location = {Montreal, Canada},
series = {NIPS'14}
}
@misc{ctgan,
      title={Modeling Tabular data using Conditional GAN}, 
      author={Lei Xu and Maria Skoularidou and Alfredo Cuesta-Infante and Kalyan Veeramachaneni},
      year={2019},
      eprint={1907.00503},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1907.00503}, 
}
@article{bellovin2019privacy,
  title={Privacy and synthetic datasets},
  author={Bellovin, Steven M and Dutta, Preetam K and Reitinger, Nathan},
  journal={Stan. Tech. L. Rev.},
  volume={22},
  pages={1},
  year={2019},
  publisher={HeinOnline}
}

@inproceedings{ping2017datasynthesizer,
  title={Datasynthesizer: Privacy-preserving synthetic datasets},
  author={Ping, Haoyue and Stoyanovich, Julia and Howe, Bill},
  booktitle={Proceedings of the 29th International Conference on Scientific and Statistical Database Management},
  pages={1--5},
  year={2017}
}

@inproceedings{kuppa2021towards,
  title={Towards improving privacy of synthetic datasets},
  author={Kuppa, Aditya and Aouad, Lamine and Le-Khac, Nhien-An},
  booktitle={Annual Privacy Forum},
  pages={106--119},
  year={2021},
  organization={Springer}
}

@article{tai2023user,
  title={User-Driven Synthetic Dataset Generation with Quantifiable Differential Privacy},
  author={Tai, Bo-Chen and Tsou, Yao-Tung and Li, Szu-Chuang and Huang, Yennun and Tsai, Pei-Yuan and Tsai, Yu-Cheng},
  journal={IEEE Transactions on Services Computing},
  year={2023},
  publisher={IEEE}
}
@article{stadler2020synthetic,
  title={Synthetic data-A privacy mirage},
  author={Stadler, Theresa and Oprisanu, Bristena and Troncoso, Carmela},
  journal={arXiv preprint arXiv:2011.07018},
  year={2020},
  publisher={Nov}
}

@inproceedings{jordon2021hide,
  title={Hide-and-seek privacy challenge: Synthetic data generation vs. patient re-identification},
  author={Jordon, James and Jarrett, Daniel and Saveliev, Evgeny and Yoon, Jinsung and Elbers, Paul and Thoral, Patrick and Ercole, Ari and Zhang, Cheng and Belgrave, Danielle and van der Schaar, Mihaela},
  booktitle={NeurIPS 2020 Competition and Demonstration Track},
  pages={206--215},
  year={2021},
  organization={PMLR}
}

@inproceedings{abadi2016deep,
  title={Deep learning with differential privacy},
  author={Abadi, Martin and Chu, Andy and Goodfellow, Ian and McMahan, H Brendan and Mironov, Ilya and Talwar, Kunal and Zhang, Li},
  booktitle={Proceedings of the 2016 ACM SIGSAC conference on computer and communications security},
  pages={308--318},
  year={2016}
}

@inproceedings{shokri2017membership,
  title={Membership inference attacks against machine learning models},
  author={Shokri, Reza and Stronati, Marco and Song, Congzheng and Shmatikov, Vitaly},
  booktitle={2017 IEEE symposium on security and privacy (SP)},
  pages={3--18},
  year={2017},
  organization={IEEE}
}

@article{ding2021retiring,
  title={Retiring Adult: New Datasets for Fair Machine Learning},
  author={Ding, Frances and Hardt, Moritz and Miller, John and Schmidt, Ludwig},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

@inproceedings{zhifei2017cvpr,
  title={Age Progression/Regression by Conditional Adversarial Autoencoder},
  author={Zhang, Zhifei and Song, Yang and Qi, Hairong},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  organization={IEEE}
}