Name
Abstract | ||
|---|---|---|
User interaction with intelligent systems need not be limited to interaction where pre-trained software has intelligence “baked in.” End-user training, including interactive machine learning (IML) approaches, can enable users to create and customise systems themselves. We propose that the user experience of these users is worth considering. Furthermore, the user experience of system developers—people who may train and configure both learning algorithms and their user interfaces—also deserves attention. We additionally propose that IML can improve user experiences by supporting user-centred design processes, and that there is a further role for user-centred design in improving interactive and classical machine learning systems. We are developing this approach and embodying it through the design of a new User Innovation Toolkit, in the context of the European Commission-funded project RAPID-MIX. |
Year | Venue | Field |
|---|---|---|
2017 | AAAI Spring Symposia | User innovation,User experience design,Active learning (machine learning),Computer science,Human–computer interaction,Artificial intelligence,User modeling,Interactive systems engineering,User interface design,User interface,Multimedia,Machine learning,User journey |
DocType | Citations | PageRank |
Conference | 2 | 0.38 |
References | Authors | |
14 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco Bernardo | 1 | 3 | 1.07 |
| Michael Zbyszynski | 2 | 32 | 6.86 |
| Rebecca Fiebrink | 3 | 281 | 36.77 |
| Mick Grierson | 4 | 3 | 2.42 |