TY - GEN
T1 - Sharing Secrets with Agents
T2 - 23rd International Conference on Human-Computer Interaction, HCII 2021
AU - Buckley, Oliver
AU - Nurse, Jason R. C.
AU - Wyer, Natalie
AU - Dawes, Helen
AU - Hodges, Duncan
AU - Earl, Sally
AU - Belen Saglam, Rahime
PY - 2021/7/1
Y1 - 2021/7/1
N2 - There is an increasing shift towards the use of conversational agents, or chatbots, thanks to their inclusion in consumer hardware (e.g. Alexa, Siri and Google Assistant) and the growing number of essential services moving online. A chatbot allows an organisation to deal with a large volume of user queries with minimal overheads, which in turn allows human operators to deal with more complex issues. In this paper we present our work on maximising responsible, sensitive disclosures to chatbots. The paper focuses on two key studies, the first of which surveyed participants to establish the relative sensitivity of a range of disclosures. From this, we found that participants were equally comfortable making financial disclosures to a chatbot as to a human. The second study looked to support the dynamic personalisation of the chatbot in order to improve the disclosures. This was achieved by exploiting behavioural biometrics (keystroke and mouse dynamics) to identify demographic information about anonymous users. The research highlighted that a fusion approach, combining both keyboard and mouse dynamics, was the most reliable predictor of these biographic characteristics.
AB - There is an increasing shift towards the use of conversational agents, or chatbots, thanks to their inclusion in consumer hardware (e.g. Alexa, Siri and Google Assistant) and the growing number of essential services moving online. A chatbot allows an organisation to deal with a large volume of user queries with minimal overheads, which in turn allows human operators to deal with more complex issues. In this paper we present our work on maximising responsible, sensitive disclosures to chatbots. The paper focuses on two key studies, the first of which surveyed participants to establish the relative sensitivity of a range of disclosures. From this, we found that participants were equally comfortable making financial disclosures to a chatbot as to a human. The second study looked to support the dynamic personalisation of the chatbot in order to improve the disclosures. This was achieved by exploiting behavioural biometrics (keystroke and mouse dynamics) to identify demographic information about anonymous users. The research highlighted that a fusion approach, combining both keyboard and mouse dynamics, was the most reliable predictor of these biographic characteristics.
KW - Biometrics
KW - Chatbot
KW - Conversational agent
KW - Disclosure
KW - Information inference
KW - Keystroke dynamics
KW - Mouse dynamics
UR - http://www.scopus.com/inward/record.url?scp=85112026542&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-78642-7_54
DO - 10.1007/978-3-030-78642-7_54
M3 - Conference contribution
AN - SCOPUS:85112026542
SN - 9783030786410
T3 - Communications in Computer and Information Science
SP - 400
EP - 407
BT - HCI International 2021 - Posters - 23rd HCI International Conference, HCII 2021, Proceedings
A2 - Stephanidis, Constantine
A2 - Antona, Margherita
A2 - Ntoa, Stavroula
PB - Springer
Y2 - 24 July 2021 through 29 July 2021
ER -