Automated robotic surgical interfaces are the future; they will provide access to life saving surgical treatment in resource limited locations such as space and the third world. In order to establish such a safe and reliable model, we must first teach robots to be able to adapt to situations and become familiar with movement pattern. Machine learning is a fast-growing field. But in order to teach the machine, you must first recreate the scenario. Currently, the field of surgery is actively pursuing improved haptic feedback and tissue models (Vapenstad et al, 2013). VR haptic feedback surgery simulators will provide an unparalleled opportunity to train surgeons and will provide the ability to perform tele-surgery (Yamamoto & Okamura, 2011). Eventually the surgeon will be operating on the patient from a considerable distance. It is at this stage that the possibilities for machine learning are at their greatest. By teaching the machine through periods of trial and error by surgeons, the machine will be able to adapt. The integration of VR technology and haptic feedback systems will provide optimum conditions for machine learning. This will provide a connection between taught and learnt behaviours. To teach natural movements, natural movements must be performed, and yet with current VR systems this is difficult given the lag in haptic feedback development. It is our wish to develop a system that will mimic reality with high fidelity, capture dynamic movements between user and machine and ultimately through significant exposure to a variety of scenarios and tasks, teach the machine to react and adapt to unpredictable situations. To facilitate machine learning, we must first optimise and enhance human machine interaction. Machines will learn from human movement in its most natural form, when it is being performed for a specific purpose and in reaction to surrounding stimuli. It is our belief that through the specific application of VR to robotics and the answering of seven questions, we can create an autonomous robotic machine.