Dimension	Item
AI experience	1. Using algorithms and methods such as Naïve Bayes, Support Vector Machine, Linear Regression, Logistic Regression, KNN, K-means, Decision Tree, Random Forest, CART, Apriori Machine Learning Algorithm, PCA, CatBoost, ID3, Hierarchical Clustering, Back-Propagation, AdaBoost, Deep Learning, Gradient Boosting Algorithm, Hopfield Network, C4.5, etc.
	2. Using frameworks such as TensorFlow, PyTorch, Keras, etc.
	3. Researching, understanding, and leveraging the following applied technologies: Text Analytics and NLP, Speech Recognition, Virtual Agents, Machine Learning Platforms, Deep Learning Platforms, AI-optimized Hardware, Decision Management, Biometrics, RPA, etc.
	4. Using semi-autonomous driver-assist systems such as active park assist, adaptive cruise control, lane-departure warning, blind-spot monitoring, etc.; or using an unmanned aerial vehicle (UAV).
	5. Using AI-based photo editors or graphic design tools (e.g., AutoDraw and Prisma), or producing hyper-realistic videos using artificial intelligence applications such as Deepfake technology.
AI exposure	1. Using an intelligent virtual assistant (IVA) or intelligent personal assistant (IPA) such as Apple Siri, Microsoft Cortana, Amazon Echo and Alexa, Google Assistant, etc.
	2. Using automatic voice recognition and generation systems (e.g., speech to text, text to speech) through instant messengers, note-taking apps, ebook reader apps, short-form video apps, etc.
	3. Using automatic image detection, recognition, and classification technologies through image search engines, smart photo libraries, online shopping apps, etc.
	4.Using automatic face recognition technology, voice biometric authentication, or a finger vein scanner with respect to security and fraud prevention, access and authentication, biometric payment, etc.