This article is part of a Technology and Innovation Insights series paid for by Samsung.
Similar to the relationship between an engine and oil, data and artificial intelligence (AI) are symbiotic. Data fuels AI, and AI helps us to understand the data available to us. Data and AI are two of the biggest topics in technology in recent years, as both work together to shape our lives on a daily basis. The sheer amount of data available right now is staggering and it doubles every two years. However, we currently only use about 2 percent of the data available to us. Much like when oil was first discovered, it is taking time for humans to figure out what to do with the new data available to us and how to make it useful.
Whether pulled from the cloud, your phone, TV, or an IoT device, the vast range of connected streams provide data on just about everything that goes on in our daily lives. But what do we do with it?
Earlier this month, HARMAN’s Chairman Young Sohn sat down with international journalist Ali Aslan in Berlin, Germany at the “New Data Economy and its Consequences” video symposium held by Global Bridges. Young and Ali discussed the importance of data, why AI without data is useless, and what needs to be considered when we look at the ethical use of data and AI — including bias, privacy, and security.
Bias
Unlike humans, technology and data are not inherently bias. As the old adage goes — data never lies. Bias in data and AI comes into play when humans train an AI algorithm or interpret data. Much of what we are consuming is influenced based on where the data is coming from and what data is going into the system. Understanding and eliminating our bias are essential to ensuring a neutral algorithm and system.
Controlling data access and permissions are a key first step to remove bias. Having a diverse and inclusive team when developing algorithms and systems is essential. Not everyone has lived the same experiences and backgrounders. Diversity in both can help curb biases by providing different ways of interpreting data inputs and outputs.
Privacy
Permission and access are paramount when we look at the privacy aspect of data. Privacy is extremely important in our increasingly digital society. As such, consumers should have a choice at the beginning of a relationship with an organization and be asked whether they want to opt-in, rather than having to opt-out. GDPR has been a good first step in helping to protect consumers in regards to the capture and use of their data. While GDPR has many well-designed and important initiatives, the legislation could be more efficient.
Security
Whereas data privacy is more of a concern to consumers and individuals, data security has become a global concern for consumers, organizations, and nation-states.
It seems like every day we are reading about another cyber-attack or threat that we should be aware of. Chief among these concerns are the influx of ransomware attacks. Companies and individuals are paying increasingly large amounts of money to bad actors in an attempt to mitigate risk, attention, and embarrassment. These attacks are being carried out by individuals, collectives, and even nation-states in an attempt to cripple the systems of enemies, gather classified information, or garner capital gains.
So how do we trust our data and information is safe and what can we do to be better protected? While there may be bad actors using technology and data for their own nefarious devices, there are also many positive uses for technology. The amount of education and investments being made in the cybersecurity space have helped many organizations to train employees and invest in technologies that are designed to prevent cybercrime at the source — human error. And while we may not be able to stop all cybercrime, we are making progress.
Data and AI for good
While data — both from a collection and storage viewpoint — and AI have gotten negative press around biases, privacy, and security, both can also be used to do an immense amount of good. For example, both data and AI have been crucial in the biomedical and agtech industries. Whether it’s COVID-19 detection and vaccine creation or the creation of biomes and removal of toxins in soil, data and AI have incredible potential. However, one cannot move forward without the other. A solid and stable infrastructure and network are also needed to ensure that we can make use of the other 98 percent of the global data available.
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