An array of new applications related to Artificial Intelligence are materializing at a rapid pace in the healthcare industry. The industry is flooded with numerous technological vendors, research analysts, and enthusiast innovators who are bridging the gap by creating predictive and prescriptive data to improve diagnosis and increase the aspects of treatment recommendations. It is of dire need that healthcare industries top-notch their AI governance in order to balance varied cutting-edge AI innovation with solutions that are worth a try. But the major question that lingers in every individual’s mind, is what does AI have to do with healthcare, where computers are given access to our information? And what does it mean for healthcare, where our health records and conversations with our doctors used by a commercial enterprise? This article further elaborates on the need for AI governance in the healthcare industry.
1. Health on track
The first feature that brings to light the necessity of AI governance is the absolute initiative to help individuals monitor their health. AI has become a vital potential in the fast pacing world. .AI helps both healthcare professionals and individuals to stay on track with their health in the most convenient manner. Technological applications encourage individuals to lead a healthier lifestyle and sustain proactive management of their health. Healthcare professionals are graced with the opportunity to better understand the routine of the people and act accordingly.
2. Ensures transparency
The second most important aspect of governing how AI systems work with healthcare data is transparency. AI clearly defines what can be used and, what cannot. For example, Imperial College London recently announced an AI project to improve early detection of ovarian cancer. To illustrate the same, a confined rule was implemented that all scans showcased will be anonymous. The computer was placed at a juncture where it was unable to detect whose scan it is analyzing. Hence, the data obtained from the same analysis was used to aid diagnosis and nothing more than that.
3. Assuage concerns
With data privacy scandals being uncovered every day, people are naturally cautious to share their personal data to be used in an AI system. The third important aspect is the art to protect your data. The data collected from varied healthcare centers are handled with the uttermost privacy and AI ensures to legally make use of the same data for diagnostic purposes only. For instance, a simple exercise used during blood donation has shown the way ahead, a text message was sent about how their blood was used – to donors and as a result it – increased voluntary blood donations. It is, therefore, an assumption that the same can be implemented to show people how medical data can help improve the diagnosis and care they receive.
4. Need to be Educated about AI
The fourth aspect of governance that AI showcases in the healthcare industry is the pathway to educate people on the appropriate use of AI. The biggest obstacle in regulating AI is ensuring everyone understands what it does, and how they can control it. The simple fact is that for all the hype around AI, very few people really understand what it is and what it does. Educating people on AI ensures, that they can anticipate and prevent misuse of their personal data and help in a smooth AI governance during any diagnostic procedures.
5. Stay in step with innovation
Last but not least, AI governance has been forced to keep up with advances in AI technology. The pace of development has caught even industry experts by surprise. It is only in the last couple of years that people have woken up to the urgent need to govern various aspects of this powerful tool and protect the privacy of people it is intended to serve.
As Laura Craft, the VP analyst of Gartner states, “AI governance is necessary, especially for clinical applications of the technology.” According to a scientific prediction by Gartner, it is emphasized that by 2021, 75% of healthcare delivery organizations (HDOs) will have invested in an AI capability that is explicitly improving either operational performance or clinical outcomes. The increased establishment of AI in HDO’s will pave a way for the need for AI governance in Healthcare.