Let us start with the common misconception that artificial intelligence is, in itself, only machine learning (ML). The buzzword gained hype for its futuristic automation of algorithmic learning without human intervention. Does this mean that AI has gained consciousness and does not further need the help of humans? Machine learning is brute-forcing intelligence that learns from data. This data is used for training, and then the algorithm learns how to treat the data depending on the function being optimized. When there’s a constant stream of data that people are creating every second, machine learning keeps churning that data and continually learning from it. But obtaining enough training data for machine learning models is a regular obstacle. Data collection is difficult since a large sample is needed to represent the whole population. Thus, a pressing concern is the source of the data being fed to machine learning and how the data is obtained. ML is data-hungry; it demands massive volumes of data, making the risk extremely obvious.
Where did they get this data? First, scraping data from open sources is another thing to be cautious of. Frequently, it is a method to build huge datasets, and numerous technologies are now available that can automate this method. However, scraping could expose a company to legal risk because the data might be subject to copyright or privacy laws. Proponents may argue that this is anonymous data, but there’s a great possibility that when two unrelated datasets are merged, they could easily identify individuals. Second, every person, location, or thing is under constant monitoring. This persistent surveillance involves watching someone or something somewhere, and devices that are used directly and indirectly are employed to obtain information. These devices send data to business corporations for storage, collection, and analysis. This data may possibly be used to study people and their environment in ways they are unaware of. Moreover, consumers seem uncertain about privacy issues concerning these devices. We find that even huge segments of a population may surrender their privacy for gain. Data collection is risky, and data misuse is a major issue. Data processing, use, and sale are typically unknown to users. Even more so, the advancement of computers and mass data technologies enabled business corporations to gather, store, and process enormous amounts of data about almost all the population and control how, when, where, and what kinds of data could be gathered. This also exploded with the advent of ubiquitous technologies such as smartphones, security cameras, and the Internet. Gathering personal data has never been this simple. Previous anonymous data is easily tracked and linked with a name. At this point, we can no longer stop such AI systems from consuming publicly available data.
What things should we consider when acquiring data? The following must be included in a company’s data retention policy:
How and where is the data stored?
What is the duration for keeping the stored data?
What is the format?
Who is authorized to access the data?
Who is not authorized to access the data?
Privacy in AI frequently refers to how data is utilized once we give it freely as a byproduct of our digital lives. Privacy means we want to regulate who can access and use our data after someone else has it. In line with ethics and values, Valmiz respects people’s data. Core ethical principles are embedded in Valmiz, a system using multi-agent design, in contrast to contemporary AI, which uses a statistical model that feeds on huge datasets and regurgitates something that only resembles a genuine AI product. For example, some use original creative works without consent to deliver a “new” product. With privacy policies and protocols in mind, Valmiz only processes a client’s own internal, organizational, and raw data to produce an enterprise-level super knowledge base. The major inputs into Valmiz are pre-validated because they come from the organization itself. Due to the nature of how Valmiz operates, we only use data that the client voluntarily provides and validates.
Without respect for the value of human privacy, we’ll live in a dystopian society. We firmly believe that we don’t have to sacrifice our freedom in order to attain a societal intelligence upgrade. Ethics and values come as a result of voluntary adherence to rules. Valmiz, right from the outset, has been very cooperative in discussing how the data is being used, and we want to be the difference we want to see.
