"Data Security & Artificial Intelligence"

Andrew J Wesolowski, Director of Operations, Electronic Recycling Association


In preparation for the 2018 CAMSS B.C. conference, we caught up with Andrew Wesolowski, Director of Operations for Electronic Recycling Association to discuss the data security through the use of artificial intelligence.

1. Before we take a look at the convergence of data security and artificial intelligence, can you first explain some of the key challenges both public and private sector organisations currently face around data security?

It's no doubt big data continues to gather more attention in every passing year. As we dive deeper into the realm of big data and cloud based storage, its certainly becomes coupled with challenges to privacy and security. While its nothing new to large organizations, it's becoming more relevant to smaller and mid-sized firms alike. We're seeing databases constantly evolving, making it difficult for security solutions to keep up with the changing demand. Generally upon receipt of large amounts of data there is a need for it to be validated to determine it's accuracy and trustworthiness, however this doesn't always occur. In addition, we see the rise in ransomware and DDos attacks which have become a dangerous threat to many organizations worldwide and possess the ability to disable a business in a matter of minutes. Another major concern exists in the prevalence of IoT devices in the vulnerability they possess by potentially being overridden and illicitly hijacked for information. When discussing IoT regulation, this also follows in conjunction and intertwines with the adaption of AI.

2. How is AI positioned to help combat these challenges?

When we talk about AI and it's role in combating threats to security and our big data, which must also regard ML. Although they are quite similar, we hope to implement the use of AI to make decisions or carry out tasks such as we do. On the other hand, with the use of Machine Learning, we plan to simply give the data to a "machine" and allow them to learn on their own. I think that in the current stages of development, Applied AI and algorhythms would be initially positioned to well adapt in the role and realm of big data and cyber security. However from a forward looking perspective, it's truly exciting how the rise of Machine Learning or Generalized AI is preparing to take it's place for the fulfillment of protection. Without a doubt, it will be remarkable when we possess abilities to allow machines to learn for themselves by simply plugging and tapping them into our world(s) of information.

3. Are there any challenges companies initially face when looking to implement AI to protect their valuable data?

Most definitely challenges do exist when we look to implement AI, I think what's broadly and initially faced is the lack of computational power and hardware (chip demand). Currently we have Cloud taking a large bulk of the workload and larger paralleled systems, however our progress may be slowed as data and algorhythm complexity grows. In order for our framework to be supported, we need to consider the time lag associated with development and engineering of more powerful or even quantum computation. Secondly, we must take into account if sufficient people power exists, does an organization possess trained individuals with core skills and understanding to manage systems that learn and work on their own? Lastly, it's my view that one of the main hurdles faced by businesses will be the element of trust in AI. In this counterpart of our advancement, progress will face obstacles such as just general understanding of what responsibilities we're putting in the hands of machines. We must also remember to give consideration to legislation --  it is very much on it's heels in keeping up with technological progress and analysis of what decisions machines will be making in regards to personal data.

4. What should IT leaders and companies of all sizes do to take the first-steps of adopting AI to prevent and react efficiently to data breaches?

As with any step of growth within a organization, firstly and most importantly we must familiarize ourselves. Getting familiar with AI and it's basic concepts is the fundamental building block of it's incorporation. With a large wealth of information burgeoning online and from our top institutions in North America, there's opportunity for everyone to ride along the cutting edge. Furthermore, businesses must ask themselves what problems they foresee AI solving for them. The process involves differentiating where the adaptability lies in protection, and how it will contribute to the mitigation of a potential data breach. In my opinion the most important contributions to an organization's success would involve a 360 degree analysis or pilot project, and deriving concrete value for the benefit with which AI aligns.

5. You will be leading a session at the 2018 CAMSS B.C. conference on September 19 in Vancouver. What do you ultimately want people to take away from this session?

This will be an exciting and informative session which will leave our attendees with a wider glimpse of development, key ideas, and understanding of this technological milestone upon us. The goal for this session is to give our IT leaders a top-down look into the up-to-date advancement of Artificial Intelligence, Machine Learning and the roles they look to play in convergence with Data Security in the future. Not only will we seek to understand the value, adaptability and implementation in benefit of our organizations. We will expand our horizons, learn fascinating facts and components which will help shape our goals and successes for the coming years.     


Andrew Wesolowski is speaking at the 2018 CAMSS B.C. conference, taking place on Wednesday, September 19 at Vancouver Convention Centre. For information on the event and to register go to www.camsscanada.com/british-columbia.