We welcome this year’s authors to HICSS 50th anniversaryand especially to the second anniversary of this new minitrackOrganizational Learning. Organizational learning involves processes of creating, transferring, modifying and retaining knowledge over time. These learning processes may occur at the individual, group or organizational levels, and involve topics that would benefit essential funct...

The argument developed in this paper can be outlined as follows: relationships are vital for growth, for adults and especially for children; to ensure that we work to maintain relationships, evolution provided for pain on separation, which stimulates behaviours designed to restore the relationship. If the separation is permanent, it is necessary to form other relationships. This requires modify...

Modern privacy regulations grant citizens the right to be forgotten by products, services and companies. In case of machine learning (ML) applications, this necessitates deletion data not only from storage archives but also ML models. Due an increasing need for regulatory compliance required unlearning is becoming emerging research problem. The requests come in form removal a certain set or cla...

today’s challenge is learning about how to live with the change instead of planning for it and the critical point that causes the organizational change programs to fail is the lack of integrated conceptual model. to face this issue, the article has a literature review to develop a holographic model. in this model. content analysis has been used in this article. theresult was a holographic model...

Machine learning has attracted widespread attention and evolved into an enabling technology for a wide range of highly successful applications, such as intelligent computer vision, speech recognition, medical diagnosis, more. Yet special need arisen where, due to privacy, usability, and/or the right be forgotten , information about some specific samples needs removed from model, called machine ...

Why does so much literature on unlearning ignore the people who do unlearning? What would we understand differently if focused those people? Much of existing argues that can only be achieved, and new knowledge acquired, old is discarded: clean slate approach. This might a reasonable way organising stock in warehouse, where room needs to created for deliveries, but it not an accurate description...

When doing learning from demonstration, it is often the case that the demonstrator provides corrective examples to fix errant behavior by the agent or robot. We present a set of algorithms which use this corrective data to identify and remove noisy examples in datasets which caused errant classifications, and ultimately errant behavior. The objective is to actually modify the source datasets ra...