What thought comes to your mind when you think about Artificial Intelligence (AI)? Is it a robot imitating human behavior? Is it a machine that could automate your work or a device that reads your brain?

AI is the capability of a machine to exhibit human-like abilities. It already exists in various fields and is transforming how we work. In the healthcare sector, AI allows better diagnosis and automated treatment suggestions.

Microsoft has used AI to detect scammers in online chats. China has built an AI app to combat poverty in its remotest villages.

AI has transformed everything, from automation to robots exceeding human intelligence. Will AI have an impact on M&E as well? Development experts believe AI has the potential to have a significant effect on M&E. It is only a matter of when and how it does it.

With the significant development of AI, M&E is all set to experience a new era! Innovations, such as data collection, processing, and validation, will transform M&E. Several organizations are already embracing other ways to implement AI.

Prominent examples include Natural Language Processing (NLP) and Object Recognition. NLP can read and analyze human-typed text. Object Recognition tracks the attendance of events or identifies human behavior.

AI has the potential to process data more efficiently and replace conventional methods. Let’s determine how AI can help to improve a myriad of M&E processes.

Natural Language Processing (NLP)

If you are among those who spend the entire day sifting through several Excel entries, NLP could be a perfect solution for you. NLP interprets text responses and matches them against existing datasets. With the integration of NLP, you would not need to review each data entry manually!

NLP is combination of computer science, linguistics and machine learning. It focuses on communication between humans and computers in natural language. Prominent applications of NLP include voice assistants like Apple’s Siri and Amazon’s Alexa.

Using text vectorization, NLP converts texts into something a machine can understand. The AI algorithms include training data and expected outputs. In this way, NLP machines connect input and its corresponding output. Using this knowledge, machines perceive which feature best represents the text.

Generally, NLP involves two types of formats, Syntactic and Semantic analysis:

• Syntactic analysis: Also known as syntax analysis. It evaluates the syntactic structure of the text and analyzes relationships between different words. It applies grammatical rules to only a group of words, not individual words.
• Semantic analysis: This analysis focuses on recognizing the meaning of language. It is the process of comprehending interpretation of words, sentence structure and signs. This allows the machines to partially understand languages in a way humans do. Since language is polysemic, this analysis is one of the most challenging aspects of NLP.

Although NLP is unequivocally helpful for M&E, it has some constraints you need to be aware of. The limitations include comprehending complex syntaxes and working with less-spoken languages :

• The NLP works best for sentences with simple syntax structures. When you add more complex phrases or longer text, the capability of AI deteriorates. Future AI could decrypt texts with complicated syntax and longer strings.
• Currently, NLP is only designed to comprehend a few major languages. For instance, this AI technology can work in English and Spanish. At the same time, it may not work for native or less-spoken languages. As AI evolves, NLP will be reprogrammed to understand more languages.

NLP apps are best-suited to interpreting misspelled answer text during mobile data collection. It can help data collectors and evaluators save time by categorizing responses. Responses are sorted by qualitative categories such as positive, negative, or neutral.

Facial Recognition and Attendance Tracking

AI helps qualitative evaluation, which can be crucial for recognizing facial expressions. On a fundamental level, AI focuses on improved attendance tracking solutions.

AI is exceptional at evaluating the people in photos in different timeframes. You can capture a group picture at the end of each meeting to track the participation. You can take a complete photo of the crowd at a larger event and later use it to estimate the number of employees.

Experts use AI to monitor human behavior to understand emotions and human feedback. The technology is quite effective in giving sentiment analysis of photos. This assists in identifying the feelings, expressions, and behavior of the concerned people.

You can understand how a client perceives products. This can help to determine which aspects need further improvement.

Sentiment analysis has matured enough for the M&E sector. AI gathers information from unstructured data and effective computing. This information could help with:

• Predictive analytics
• Evaluating buyer response in the stock market,
• Managing employee management.

AI-based sentiment analysis has many practical uses. For instance, you can get customer service tickets in the queue to resolve negative feedback. You can track how the modifications of a product impact clients’ attitudes. An example is you can observe how customers respond to adding new features to the product.

Object Differentiation

Did you ever have difficulty differentiating two photos that looked similar? If so, AI can help you by effectively telling the pictures or objects apart. Whether a small business or a multinational company, AI removes humans’ need to differentiate the images.

You can leverage AI to develop mobile applications that track supply delivery. AI helps you to track with increased speed and reduced costs. For instance, let’s assume a field staff member submits you a photo of medicines and syringes.

You would not need a human to check medicines or syringes off a list of delivered items. Since no human presence is required, AI would help you to save costs.

The Bottom Line

Whether sorting quantitative data, differentiating images, or facial recognition, AI is a game changer for the M&E sector. Its importance lies in speeding up data processing and eradicating human interventions.

AI is an essential creation of the technological area that will revolutionize M&E. The primary appeal of using AI for M&E lies in accessing high-quality and accessible data. Reputable companies such as Delta Monitoring help you to explore limitless possibilities in the M&E field.

The post How can AI help in Monitoring & Evaluation? appeared first on Big Data Analytics News.