In the era of industry 4.0 and the rush to digitization, big data are the raw material from which we can extract knowledge. However, they are not always used at the best o their capability and the current news is full of scandals about privacy violations perpetrated by big tech companies. Despite this, it is reductive to define big data and their use as always unacceptable, especially when they can help us live better and longer.
Currently there is an algorithm that decides what to show and what to hide on our devices (special kind of advertisements or only some types of news). This system should be transparent and accessible. If we want to benefit from being part of this new global network we have to accept that our data is stored somewhere and is out of our control. Governments are taking an interest in this issue in two ways: by preventing the collection and centralisation of data or by creating new and very complicated laws on the use and sale of data. But this approach does not help us find new knowledge and create new insights into our lives. Big data themselves are incomprehensible; they are like huge mountains where software are the digging machines and analysts are like miners who can conduct researches from public data for private purposes (such as analysis of habits to trace an individual’s geographical position). A possible ethical approach to big data is the exact opposite; starting from private data in order to achieve a public purpose (in the case of having access to a company’s data that proves they are out of step with environmental protection laws). Transparency and accessibility are therefore key elements in improving living conditions. The problem with privacy is that the currently solutions that are proposed are simple ones and not the best solutions for everyone, and it is only on the basis of transparency that a common trust can be built.
A single patient during a one-day hospital can generate up to one hundred million data points through the medical equipment that monitors him. This data can be shared with doctors from other hospitals even on other continents and come back to the starting point full of new information and insights. This collective knowledge, assisted also by artificial intelligences, helps to diagnose better, faster and more accurately.
A first ethical and proactive application of big data to Italian healthcare is proposed by the platform ‘ThatMorning’. A search engine that indicates the best hospital to go to when a certain pathology is given. Developers of ‘ThatMorning’ cross-referenced data from health facilities such as the number of services provided, degree of modernisation of medical equipment, degree of specialisation of physicians and nurses, the results of the interventions and the economic budgets.
So that the app can lead patients to the most suitable facility for the treatment of their illness. But not only this, the platform provides in also a space where patients can write a personal diary to keep track of their own clinical history and the possibility to read some ‘stories’ written by other patients who are experiencing the same disease so as to offer a network for psychological support.
What are the alternative therapies?
Where do you get access to these treatments?
Who are the experts for this specific disease?
These are just some of the questions that go through the minds of patients and doctors themselves who are always looking for the best way to treat a disease. As we have already seen, the data produced by hospitals are constant, full of meaning and profound. Not only through the machines connected to the patients, but also through the story of the disease by patients and doctors, by the experience gained in the ward, by the family of patients. All this make data more numerous (called Big Data) and more diversified. How can one extract knowledge from such a mass of data? For now there are two solutions; the first concerns the hiring of thousands of analysts to clean, label and sort these data. With all the limitations of the case like the impossibility to have an answer in real time and the enormous sum to spend in order to finance the entire process. The second concerns the application of artificial intelligence and blockchain. IA can be applied in the data collection, forecasting and processing phases. The ultimate goal is to create an AI specific for this field (as well as specific languages for scientific fields) eliminating the ambiguities that arise from the application of the same artificial intelligence to different fields. The potential of this technology allows to analyze billions of data points to have almost certain predictions and create new perspectives. Obviously in such a particular field of application quality data are needed, one of the basic rules of this technology is: ”the more the data entered is relevant, the more relevant the response will be”. The incredible thing is that for AI even the wrong answers are relevant; the fact that a particular medicine did not serve the purpose of curing a disease is of fundamental importance for a more correct diagnosis. Many doubts are raised about the privacy of this sensitive data and the intellectual property of successful trials and those that have not. Blockchain technology can be used to clarify these doubts; once something is published through the blockchain, it will be validated with a ‘digital stamp’ which will let everyone know who is the author of that pubblication and who has conducted that experiment. The blockchain also provides an immutable list of transitions so that when information is shared with someone, the track of this transition remains. AI and blockchain are potentially revolutionary technologies but only if used to solve important problems, and the most extraordinary thing is that it is happening now. Providing not only information and knowledge but also hope and tranquility.
Big data are not only cure, but also prevention. An algorithm was able to predict the outbreak of Ebola nine days earlier than the World Health Organization. And it’s amazing that thanks to this technology we could have used all that time to contain the spread of the virus. Another possibility in recent months comes from the video game industry; to a sophisticated virtual reality game was added a big data layer, which allowed the simulation of complex surgical procedures. A novice can use these games to exercise and, perhaps, make their first fatal mistake on a virtual patient. Not to mention that these ‘serious video games’ can be customized according to the needs of the individual patient and be adapted to a myriad of different cases.
The potential of Big Data is limited to the user’s imagination. As very often has happened throughout recent history, the technology has been blamed instead of the way it is used. The choice is always in our hands, control is always in the hands of someone rather than something. And the hope is always that that someone is moved by integrity and morals.