(Q4684)
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Statements
instance of
project
0 references
impact goal
thought leadership
for
PersonalData.IO
main subject
algorithmic accountability
reference URL
https://medium.com/personaldata-io/inferring-distance-from-bluetooth-signal-strength-a-deep-dive-fe7badc2bb6d
0 references
connecting communities
with
developer community
nonprofit
interested in
data protection
0 references
outreach
with
journalist
in
worldwide
for
PersonalData.IO
0 references
thought leadership
main subject
Bluetooth Low Energy
suggestion
IndoorAtlas
0 references
official website
http://github.com/PersonalDataIO/CoronaRiskScoring
0 references
interested in
Corona-Warn-App
0 references
TraceTogether
0 references
Stopp Corona
0 references
D'scover
0 references
Aarogya Setu
0 references
Rakning C-19
0 references
WeTrace Philippines
0 references
ProteGO Safe
0 references
HaMagen
0 references
StopCovid
0 references
Smittestopp
0 references
eRouška
0 references
MahaKavach
0 references
StopKorona!
0 references
SwissCovid
0 references
1point5
0 references
VírusRadar
0 references
COVIDSafe
0 references
NHS COVID-19
0 references
Alerta Guate
0 references
NOVID
0 references
Care19 App
0 references
Sonar-X
0 references
concerns
contact tracing application
0 references
see also
Bluetooth Low Energy
0 references
partner
PersonalData.IO
0 references
prospect
AlgorithmWatch
for
partnership with
0 references
Derechos Digitales
for
partnership with
0 references
The Citizen Lab
for
partnership with
0 references
OHCHR
for
partnership with
0 references
Privacy International
for
partnership with
0 references
Amnesty Security Lab
reference URL
https://www.middleeasteye.net/news/coronavirus-qatar-tracing-app-flaw-exposed-one-million-peoples-details-says-amnesty
0 references
AppCensus
comment
while AppCensus can't really help with risk scoring directly, they can help with auditing the functioning: input data as well as what gets exfiltrated, both through the app and through Bluetooth
0 references
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