The Impact of Machine Learning

Machine Learning, artificial intelligence and data mining may seem like abstract concepts that have little to do with the day to day functions of your small to medium sized business. But Gartner has officially added machine learning (ML) to their Hype Cycle for Emerging Technologies. This means there is enough research, resources and momentum behind machine learning that it could potentially redefine buyer, supplier and customer relationships for any business.

Power can be found in machine learning’s ability to analyze the amount of data businesses produce. Impressive developments are being made in virtual reality, artificial intelligence, ML and similar smart technologies. While the concepts are related, there are some important distinctions.

  • Artificial Intelligence: Enables machines to increase their abilities to sense, reason, act and adapt to the real world. A machine is deemed artificially intelligent if it can do things normally associated with human intelligence.

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  • Machine Learning: A component of artificial intelligence that provides computers the ability to learn without being explicitly programmed, by heavily relying on statistics. The statistics help develop the machine’s self-learning algorithms. The algorithms then allow the machine to act or think without being prompted to perform specific functions. There are two main categories machine learning can be divided into–
    1. Supervised ML: Typically entails using a set of features to predict an outcome. The supervised algorithm analyzes labelled data and produces an inferred function.
    2. Unsupervised ML: No labels are given to the learning algorithm leaving it on its own to find structure. Unsupervised learning may be the ultimate ML goal in itself.

Current Developments

From potential life-altering medical advances, to smart business tools, machine learning can be utilized to block or permit critical messages.

  • Boomerang: An e-mail composition tool that uses machine learning to determine a broad set of factors that contribute to an e-mails probability of response. Important for successful marketing campaigns, and when reaching out to sales prospects.

Much like how algorithms have been used to block mass amounts of spam e-mails from being delivered to your inbox, machine learning could soon block irrelevant content published to the web.

  • Brain and Spinal Cord Injuries: A machine learning software is being developed that could be used to restore function to those with brain or spinal cord injuries. The hope is that there would be a brain to computer interface via an implantable device.
  • Espionage: The NSA (US National Security Agency) and CSIS (Canadian Security Intelligence Service) use ML to gather intelliegnce and analyze internet traffic. The ML will look for patterns of behaviors that may indicate terrorist activitiy.

How Machine Learning Will Impact Small Business

Machine learning is sure to impact your business in passive, uncontrollable avenues. It may not be apart of an explicit digital strategy you choose to implement internally, but your online content, e-mail campaigns and SEO (search engine optimization) will likely be impacted.

  • Marketing: Pinterest and Yelp already use machine learning to display relevant content to their users. Since Google depends greatly on user satisfaction it is sure to use machine learning to improve the quality content it delivers via search queries. That means it is almost certain to have an influence on your search engine optimization and quality of your online content.
  • Banking: Banks are streamlining some of their processes by incorporating technology. The process of directly depositing a cheque by taking a picture When a business owner is seeking funding from a bank, the bank uses a standard set of criteria that must be met in order for a loan to be approved. With machine learning, it may be possible to review much more data and various scenarios that could improve a client’s credit-worthiness. Machine learning could review Yelp scores, social media activity, and real-time shipping trends to see a more accurate profile of a client.
  • Productivity Tools: User behavior is monitored in several ways already through technology. Analysis of such behaviors can help identify who collaborates best together, who is being more productive and who could stand to be reprimanded.
  • Cyber Threats: Leveraging machine learning can prevent and protect users from cyber criminals and cyber attacks.

Things to Consider

As the quantity of data we produce as businesses grows over time, so too will our computers’ ability to process, analyze and learn from that data. The competitive advantage will lie in what we do with that analysis. We are operating in a world where written code developed by humans is full of bugs and requires diligent patch management. Security issues, data breaches and privacy are issues all users and businesses face. How will the industry account for those same issues when its developed by a machine with its own intelligence?