AI and Home Security: What To Know
In recent years, artificial intelligence and machine learning have been rapidly integrating into other types of technology and breaking ground in different industries. Considering some of its issues and the risks it poses, AI’s involvement in home security might be a cause for concern.
However, there are certain advantages to surveillance systems enhanced with AI — such as improved threat detection and automated security — that make them stand out from traditional systems. Read on to learn more about how artificial intelligence is reshaping security technology and what you should know before investing in a security system for your home.
How AI integrates with home security systems
The role of AI in security systems is to alert homeowners of potential security threats and help them manage incidents with greater accuracy and effectiveness than traditional systems. Some of the features that contribute to this include:
- Video analytics: AI security cameras have sensors that allow for the simultaneous recording and processing of a live feed. Without this, footage needs to be manually reviewed and analyzed. Thanks to this feature, AI home security systems are able to perform:
1. Facial recognition and identity verification (identifies threats by consulting with a database of known individuals)
2. Motion detection (differentiates between objects, animals, vehicles, etc.)
- Predictive analytics: Includes pattern recognition and behavior analysis, which can trigger alarms and notifications when abnormal behavior is detected.
- Voice recognition: Allows homeowners with smart home security measures in place to give their systems voice commands.
- Home automation: Smart home systems connect household devices like locks, lights, thermostats and water heaters to your security system.
AI-powered vs traditional home security systems
Traditional home security systems have always depended heavily on humans performing the tasks now handled by artificial intelligence. The following table lists some key differences between both types of systems, including how they operate and their potential results.
Features
Traditional security systems
AI-powered security systems
Monitoring
Footage is manually reviewed by operators; prone to errors and oversights
Live footage is scanned and analyzed in real-time 24/7
Threat detection
Could lead to missed threats or false alarms depending on how experienced and alert an operator is
Potential threats are identified based on an objective analysis of the footage; usually more accurate
Response to incidents
Operator reaction times and vigilance will determine how quickly owners and authorities are alerted
Automated alerts and notifications are triggered by anomalies and unusual activity
Concerns with artificial intelligence in home security
Although artificial intelligence has certainly made improvements to home security technology, it isn’t without flaws or limitations. Below we list some of the common issues with AI and machine learning that could impact the functionality of home security systems.
Biases and discrimination
Algorithms can have their own biases even if they were not designed that way on purpose. When designing an algorithm, the creator’s values will inevitably become part of its code.
Within the home security field, biases against certain groups of people can lead an algorithm to needlessly trigger alarms or contact the authorities because it considers them a security threat. And paired with other issues like automation bias — our tendency to automatically trust decision-making algorithms based on the perception of them being unprejudiced and undisputable — they pose a risk to these groups and anyone incorrectly perceived as a threat.
Decision-making based on correlations
Many AI algorithm models use the correlations they can establish within their datasets to further analyze and generate information, as well as to make decisions. Because they process information according to the data they have been fed or that they have mined, they can arrive at incorrect or baseless conclusions and act accordingly.
This can be particularly problematic for the home security industry, as AI technology with biased algorithms could be integrated into security systems and, as a result, make unfair assumptions about certain individuals or situations.
Lack of privacy
With AI-powered security systems performing tasks like scanning and analyzing live footage on a 24/7 basis, as well as pattern analytics, some may be concerned as to how much of their personal data is stored and how much of it security companies can access. Moreover, with issues like hacking, it’s reasonable to worry about how much of this data can be stolen and shared by criminals.
Summary of Money’s guide on AI and home security
- Security systems enhanced with artificial intelligence provide greater accuracy and efficacy in preventing and managing security threats, giving homeowners added peace of mind.
- AI has improved on home security technology through features like video and predictive analytics, voice recognition, home automation and more.
- Traditional security systems rely on the expertise and alertness of human operators, which leaves greater room for error and false alarms.
- AI-powered security systems have flaws and limitations such as inherent biases and discrimination, decision-making based on correlation and potential privacy breaches.