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Big data and data ethics

by | May 16, 2022 | AI and machine vision | 0 comments

The use and potential of Big Data is increasing day by day, as is the debate about data ethics. The line between good use and misuse or abuse of data is very thin. Technology is not the problem, but how we use it and whether this use adheres to criteria of responsibility. Big Data has multiple uses that contribute to the development of our society in areas as diverse as medicine, sociology, urbanism or economics, in addition to numerous corporate and commercial uses.


At PICVISA, for example, we have been helping recycling plants increase their productivity with technological solutions capable of generating a large amount of data for more than 20 years. Our ECOFLOW solution, a flow analyzer based on Artificial Intelligence, applies a deep learning algorithm to an artificial vision system to allow a perfect classification of the materials to be recycled and obtain valuable data for customer decision making. This is what our new DATA+ service takes care of.

The DATA+ service allows recycling plants to be 100% digitized and connected to Industry 4.0 and uses Big Data to offer solutions that increase the control, efficiency and benefits of these plants by optimizing all stages of the process. DATA+ optimizes resources and times, eliminates manual processes, allows a clear visualization of data, reduces permanent costs (OPEX), increases process reliability by minimizing human errors and allows a greater speed of reaction by offering information in real time. PICVISA will present this technological solution at IFAT 2022, the world’s leading trade fair for water, wastewater, waste and raw materials management, which will take place in Munich from May 30 to June 3.


The use of the data that, in our case, the DATA+ technological solution provides must follow the same ethical criteria that must be implicit throughout the life cycle of Big Data, both in the collection of the data and the algorithms used to do so. Keep in mind that Big Data is not always accurate or objective. The data may be poorly extracted, mismeasured, or misinterpreted because the algorithms used for its collection were wrong. And most importantly, later this same data can be used in the wrong way.

The management of this data is becoming increasingly important. Do not forget that, in the digital age, trust in an organization is also measured, and increasingly, by its way of governing and managing data, algorithms, machines … This trust is articulated mainly by the security, quality and accuracy of the data, its protection and the integrity in its use. In this sense, the European Data Protection Regulation (GDPR) regulates, since 2018, some of these aspects: collection (with authorization), management (with protection) and its use (with authorization and for lawful uses).


The debate around the ethics of data is much broader and deeper if we talk about Artificial Intelligence, which is the technology that really feeds Big Data. And this is where people come back into prominence. In fact, experts from MIT (Massachusetts Institute of Technology) talk about Machine Teaching instead of Machine Learning, thus focusing not on machines, but on the people who teach them to make good decisions taking into account data, programmed algorithms and their own learning (Machine Learning).

Thus, when talking about Artificial Intelligence, the debate is how to get machines to obey ethical criteria and pursue the common good. Although often explicit, the problem is not whether robots will replace people in many jobs or tasks. This is a collateral issue that barely overshadows the underlying problem: the risk of the uncontrolled development of Artificial Intelligence. This question was already outlined at the time by the scientist Stephen Hawking, and has also aroused the interest of businessman Elon Musk (Tesla and SpaceX) or former US President Barack Obama, who was one of the first to warn about the issue and who even designed a national strategy in this matter.

Some countries have aligned themselves in this line, although for the moment only academically. In other words, the debate on data ethics has not been translated into legislation and is limited to the existence of some codes of good practice at the international level, led by universities and organizations around the world. In this sense, specialists demand, to avoid malicious uses of Artificial Intelligence, a greater commitment and collaboration of governments with researchers and the development of new regulatory and ethical frameworks that do not slow down technological development.


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