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5 minutes Q&A - Unlocking the Power of Artificial Intelligence for Precision Medicine with Privacy-Enhancing Technologies
Prof. Jean Louis Raisaro, CHUV-UNIL, assistant professor of Biomedical Informatics and Data Science at the Faculty of Biology and Medicine and the head of the Clinical Data Science Group at the Biomedical Data Science Center
Wednesday, Oct. 11, 2023 · 1:50 p.m. · 09m 54s
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yeah i see alright hand that you sell out of it i think it
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would be really interesting tool so i have a question about secure multiparty computation
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a long wrong but the way i understand it boards um is that it's based on the assumption that the different parties
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will never clued yeah because of all the parties can do
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they can they can uh uh quite a description case saints case
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so well and tractors how do you decide what is
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an appropriate number of parties such that they want clued
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yeah so so i'll in the approach we we design we
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use the the so called any trust the right model were
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all parties but one can conclude if you have one but doesn't colour the system is secure
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so the more parties you have the more purely the system is more secure
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but how to get to the exact number in fact it's like i'm talking say
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you know like fine for like i was on any particular cases you you just need it's you just need and minus one
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so and minus one can conclude and and one one uh you see what i mean
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to threshold on and what is the minimum number of parties that don't have to go to
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these guys would be one i understand mathematically but um what i
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don't understand and practised how do you go about deciding on a number
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and not and number just um like um
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i mean even if it's an minus one right yeah i mean still check of the situation what does doesn't hold on tractors
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right
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have some ten yeah i think in the end there's a there's always some legal protection around
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that so that's what what happen in reality we're uh we have to make contracts were people
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agree to knock on wood somehow right into not sure if
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you really don't okay uh that's oh so technically the system
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preserve security as long as there's one party that that does include with the others
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even if all the others are compromised uh but practically uh how do we ensure this is through legal code
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okay and then in your applications with the whole school how many parties would use typically
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uh in the application i showed you the it's it's the five universe documents with
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so the rebar little bows and geneva so five party answer yeah five okay yeah
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but this is it's i mean theoretically it's unlimited rights really okay
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at as many times as you want yeah okay they give him
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um but i must say it's yes
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and how beautiful presentation i just so one question um about the
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slide you showed of for the um the that most of them
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for the the the production information comes or switzerland uh is the solution does this one that you use
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a solution uh accept to the to the you all
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read it so o. e. does your review of the
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the two solutions to go no i think it does kind of the feedback
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you gave on the approach right we're to essentially the the whole trick was to
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to never have the the corruption gene pool uh_huh uh so
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this was basically guaranteeing that there's no way of decrypt doing
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unless all these editions involved in the process agreed to to
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do that right so as long as they these under interruption
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this can be consider anonymous so that what is that what is it back uh_huh and this was instrumental also too
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a move forward also with canton or um
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protection authorities and ethics
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come up that you can
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any other questions that nice i have one question still yes i'm new
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here see if we have a lot of people working on has a ah
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keychain so we i i often hear people around saying oh
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yes meeting tonight and there's not enough data unless it yes it's
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a problem but i was wondering if this privacy in your field
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one of the main issues are they also other factors that uh
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need to gauge and not being shane as much and yeah domain as i mentioned before i think there is a
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that more of a challenge that we have to change like this data ownership feeling right so we're done
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there's a lot of back at it academic competitions right so who on b.
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b. s. everyone just want to exhaust any possible question before you can have how
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and uh so so the and this is a problem right so uh i think
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uh and that doesn't have to be good price so so i
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think this is one problem and also because of their decision especially
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seen in uh in health care as i mentioned before like they are
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like we award data is collected through proprietary systems than
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and every property system as his own way of storing and modelling uh the uh the semantics of the data
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so there's a lot of effort that has to be put before you can put any federated system place right on mapping the
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that constant yeah and they're they're huge initiatives in europe uh
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to to to map these to a so called common become models
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um to to you know really try to sort of the the
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pro right uh_huh it's a lot of manual manual work into that
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and a lot of data that is out there that we're not using other because it's that's exactly
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exactly yes especially if you go also have outside if you have i guess he that to other countries
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less developed countries also i think yeah even more states i think
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it's where light like cadillacs could have a great impact liking standardisation
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uh i think are the for example structuring yeah unstructured data
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and try to might be up to two semantic standards this this is something uh_huh
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useful and not that awful the and interesting and yeah
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ah yes okay thank you very much for having many interesting topics
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and of course you can delve into the details and different
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technologies at a poem controlled by i have more say pragmatic
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uh yeah action action hospitals in switzerland okay definitely be confined
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in agreement we can find the third trustee party and we
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can provide data and these guys can train in the commonplace
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unless you think about some i would say that ownership or
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whatever commercial but in make okay so it's it's let let let let's just need to get these discussion out of this but
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i'm more concerned about the the phone aspects get talking about
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performance data instead of the different hospitals like will but different equipment
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different equipment is categorise the like different resolution like different sensitivity yeah
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by different parameters and its concerns
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everything from microscope to whatever imaging device
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and here you might think okay the protected data incidence of that um but you can clearly understand that
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the the train the models on the different take originating from different sensors say let's call it looks at
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you might have much more she'd use concerns in their need of shrink his data
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rather than just protecting privacy and your simple standardisation probably format of the
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data will not help much if the data is a lot different physical nature
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yeah and here my mean my my personal doubt when i started to sink a about all this application
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it's great it's cool it's still have it but basically even hospitals would be the you you provide them privacy
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protection protocols but whether it's the useful and practical and can put magically
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practical that uh if we use unit you should will converge to the data
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we get from different sensors yeah no i think i agree with you so
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i i think uh this doesn't solve the problem so uh it it's uh
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i think what what will be it's it's a complimentary solution if you want to
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to centralise india i think's improvisation will not disappear a bigger country but not disappear because
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as you mentioned there are situations in which further it under
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any would cause more harm in terms of introducing bias or
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uh uh and things that you cannot leave and monica or because you don't have access to the original data
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uh what i what i think is that it could be
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a way to facilitate some expose initial exploration of beta before central
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position or or caring go out uh uh you know simple
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analysis or training maturity models where you are pretty sure about standardisation
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um but of course is not is not the do both solution that will
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um you know substitute to traditional beta sure i think i think the two approachable
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quite this is just that we if we want to driving to centralise data sharing
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especially across borders the stakes really really mark uh in the eh
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speech and i i shortly before they this whispers eyes at network
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which is currently adopting morse improvisation on trusted research environments like which a lot of
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uh access control security even with that it takes one year for people to agree
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uh to to to sign contracts and so on so imagine these at the international scale
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so i think federated learning at federated analogies can play a role in sort
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of accelerating the first access to the data but of course it is not final
Conference Program
(Keynote Talk) Privacy-Preserving Machine Learning : theoretical and practical considerations
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Oct. 11, 2023 · 7:55 a.m.
2509 views
5 minutes Q&A - Privacy-Preserving Machine Learning : theoretical and practical considerations
Prof. Slava Voloshynovskiy, University of Geneva, professor with the Department of Computer Science and head of the Stochastic Information Processing group
Oct. 11, 2023 · 8:40 a.m.
Enabling Digital Sovereignity With ML
Vladimir Vujovic, Senior Digital Innovation Manager, SICPA
Oct. 11, 2023 · 8:44 a.m.
5 minutes Q&A - Enabling Digital Sovereignity With ML
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Oct. 11, 2023 · 8:58 a.m.
Privacy-Enhanced Computation in the Age of AI
Dr. Dimitar Jechev, Co-founder and CTO of Inpher
Oct. 11, 2023 · 9:01 a.m.
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5 minutes Q&A - Privacy-Enhanced Computation in the Age of AI
Dr. Dimitar Jechev, Co-founder and CTO of Inpher
Oct. 11, 2023 · 9:20 a.m.
Privacy by Design Age Verification & Online Child Safety
Dr. Onur Yürüten, Head of Age Assurance Solutions and Senior ML Engineer in Privately
Oct. 11, 2023 · 9:26 a.m.
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Oct. 11, 2023 · 9:41 a.m.
(Keynote Talk) Biometrics in the era of AI: From utopia to dystopia?
Dr. Catherine Jasserand, KU Leuven (Belgium), Marie Skłodowska-Curie fellow at Biometric Law Lab
Oct. 11, 2023 · 11:06 a.m.
5 minutes Q&A - Biometrics in the era of AI: From utopia to dystopia?
Dr. Catherine Jasserand, KU Leuven (Belgium), Marie Skłodowska-Curie fellow at Biometric Law Lab
Oct. 11, 2023 · 11:42 a.m.
AI and Privacy
Alexandre Jotterand, CIPP/E, CIPM, attorney-at-law, partner at id est avocats
Oct. 11, 2023 · 11:48 a.m.
5 minutes Q&A - AI and Privacy
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Oct. 11, 2023 · 12:06 p.m.
Preliminary Pperspectives on the Ethical Implications of GenAI
Julien Pache, A Partner at Ethix and Venture Partner at Verve Ventures
Oct. 11, 2023 · 12:12 p.m.
5 minutes Q&A - Preliminary Pperspectives on the Ethical Implications of GenAI
Julien Pache, A Partner at Ethix and Venture Partner at Verve Ventures
Oct. 11, 2023 · 12:30 p.m.
AI & Media: Can You Still Trust Information
Mounir Krichane, Director of the EPFL Media Center
Oct. 11, 2023 · 12:32 p.m.
5 minutes Q&A - AI & Media: Can You Still Trust Information
Mounir Krichane, Director of the EPFL Media Center
Oct. 11, 2023 · 12:54 p.m.
(Keynote Talk) Unlocking the Power of Artificial Intelligence for Precision Medicine with Privacy-Enhancing Technologies
Prof. Jean Louis Raisaro, CHUV-UNIL, assistant professor of Biomedical Informatics and Data Science at the Faculty of Biology and Medicine and the head of the Clinical Data Science Group at the Biomedical Data Science Center
Oct. 11, 2023 · 1:22 p.m.
5 minutes Q&A - Unlocking the Power of Artificial Intelligence for Precision Medicine with Privacy-Enhancing Technologies
Prof. Jean Louis Raisaro, CHUV-UNIL, assistant professor of Biomedical Informatics and Data Science at the Faculty of Biology and Medicine and the head of the Clinical Data Science Group at the Biomedical Data Science Center
Oct. 11, 2023 · 1:50 p.m.
Genomics, AI and Privacy
Julien Duc, Co-Founder and Co-CEO of Nexco Analytics
Oct. 11, 2023 · 2:01 p.m.
5 minutes Q&A - Genomics, AI and Privacy
Julien Duc, Co-Founder and Co-CEO of Nexco Analytics
Oct. 11, 2023 · 2:18 p.m.
How trust & transparency lead the success of an Idiap student's Master's project in fraud detection
Raphaël Lüthi, Machine Learning and AI Lead at Groupe Mutuel
Oct. 11, 2023 · 2:22 p.m.
5 minutes Q&A - How trust & transparency lead the success of an Idiap student's Master's project in fraud detection
Raphaël Lüthi, Machine Learning and AI Lead at Groupe Mutuel
Oct. 11, 2023 · 2:38 p.m.
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