Implementing responsible AI from the start

Digital Pathways’ Colin Tankard looks at how we reap the rewards of AI while avoiding the risks.

Artificial intelligence (AI) and machine learning (ML) are two very hot buzzwords right now and often seem to be used interchangeably. They are not quite the same thing, but the perception that they are can sometimes lead to confusion.

Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes, without being explicitly programmed.

AI is the process of simulating human intelligence, using machines, especially computer systems. The process includes learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction.

In smart buildings, AI is already being used to control the environmental needs of the people working within the building. For example, monitoring the volume of people in any area and using this intelligence to decide if ’air-con’ should be switched on or if the lowering of shades or opening of windows will suffice.

Another example is the controlling of the smart building environment outside of hours, by counting the number of people in the building, or noting when unusual events happen, and acting accordingly.

All of this, and more, is with us today and will continue to expand into our daily business and personal lives.

Data security

Although the benefits look good, there is a fear that such AI programs could ’go rogue’ and turn on us, or be hacked by other AI programs. Hackers love artificial intelligence as much as everyone else in the technology space and are increasingly using AI to improve their phishing attacks. The need for innovative and robust data security therefore becomes even more important to the management of the smart building than it is at present.

Read the full article here in Smart Cities World