How Data Annotation Helps Security AI Developers Overcome Bias
Security systems powered by computer vision based AI models have the potential to make public spaces safer and private property more secure. By automating aspects of security monitoring, AI equipped cameras act as a force multiplier for security staff, ensuring that effective surveillance is in place at all times.
However, this promising technology still needs to navigate a range of complex problems before it becomes a feature in everyday spaces. First amongst these issues is overcoming the biases inherent in machine learning models. When AI systems have the capacity to be discriminatory or act in a manner that has legal implications, accuracy and objectivity are of the greatest priority.
This blog will highlight some of the security AI applications currently being developed and deployed. We will then look at key causes of bias that are often present in AI training data. Partnering with annotation service providers, like Keymakr, can help security AI developers meet these pressing challenges.
AI powered security applications
Developments in machine learning has begun to filter through to a number of use cases in the security sector:
- Emotion Recognition: AI models have the capacity to recognize emotional states. By identifying individuals that are displaying emotions that are inappropriate for a specific environment, AI systems can alert security staff to potential issues.
- Facial Recognition: Correctly IDing individuals can be a powerful tool for security systems. Facial recognition AI makes this process automated and fast.
- Person tagging and analysis: Models can use datasets annotated with skeletal markings to track potential threats across multiple frames of video, or they can identify unusual body language and movements, catching problems before they escalate.
- Object Recognition: Cameras have the capacity to recognise dangerous objects, such as guns or knives, acting as an early warning system so that security forces can respond more rapidly.
Diverse populations
The use cases set out above must be able to function in a wide range of settings and cultural contexts. AI that is trained predominantly with images of humans from one ethnic group will not perform effectively when asked to operate in environments that feature diverse skin colours and appearances.
In the case of facial recognition systems this could lead to misidentifications, which could have serious negative consequences for individuals. By annotating image and video data featuring a diverse and representative range of people, annotation services can help security AI developers to overcome these challenges.
Cultural differences
Different cultural practices can also impact security AI functionality. Across regions individuals may interact differently, and exhibit different forms of behaviour publicly. Failure to capture this complexity in training data could lead to emotion recognition or behaviour analysis AI systems misinterpreting movements and expressions.
Image quality
In the real-world security AI models may have to cope with lower resolution CCTV footage, or images in which objects are occluded or less visible. Failure to function when faced with these challenges could lead to dangerous objects being missed. Data annotation services can collect image and video data that reflects a variety of image qualities, helping to ensure that AI models are trained with robust datasets.
Light and weather conditions
Low visibility weather and/or low light conditions can affect the performance of AI powered security systems. Annotation providers can help developers to ameliorate these issues by creating image and video data that reflects diverse visibility conditions. Keymakr has in-house data creation facilities that allow developers to access training data that meets the specific needs of their project.
Overcoming bias with data annotation outsourcing
Security AI projects can benefit from collaboration with image and video annotation specialists. Keymakr’s skilled annotation team and unique project management options mean that demanding annotation tasks are completed on time, and to a high level of precision.
Contact a team member to book your personalized demo today.