AI Augmentation and Human Collaboration with ethical governance needs to be transparent, and accountable ensuring privacy in society by building public trust.

Reinforcement Learning (RL) and Machine Learning (ML) transfer learning builds on acquired problem solving to interconnect to problem solving helps reduce production time.

AI Natural Language Processing with the use of Chatbots can detect through sentiment analysis positive, negative, and neutral tones. Computer Vision can detect object and assist in Security ID, Self Driving (UAV)s, and collaborative robots used in manufacturing. Ethics and Bias are concerns with programming algorithms with preconceived perspective and perceptions that could lead to stereotypes of all kinds. AI will help with figuring out or detecting its own bias with counter programming. AI Seems intuitive and ideally common-sense approach to greater good. 

Artificial intelligence is expanding as seen in self-driving cars and computers moving further in Machine Learning and Deep Learning. Neutral Networks and Deep learning drive cars and other automated manufacturing with greater reliability and capacity. Machine Learning (ML) can be supervised, unsupervised, or reinforcement learning.

Skill Trade Critical Thinking starts with good communication skills which is often with your team and even yourself. The Critical Thinking Problem Solving process is 1st Identifying the problem, 2nd checking accuracy and validity, 3rd take alternate perspective, and 4th take informed action. Communication throughout the organization needs to be clear to decision makers to be most effective and efficient. 

Apprenticeships for skill training development rely on integration of conceptual problem-solving skills. Interdisciplinary Instruction involves troubleshooting, critical thinking, and problem solving needed for business.

Learning Trades with New and Newer Technologies can be used in Online environments that might not be available on-site. Contextual learning activities lead to transferable skills and lifelong learning.

Learning Skills for Trades requires reasoning through curiosity and reflection using logic mathematical and analytical thinking. Instructing students with the required content introduces the required skills, application of observable demonstration of learning through labs and testing give students real learning outcomes. With interaction of evaluation grading of learning allows the students to become IDEAL problem solvers.

I-dentify the source of the problem.

D-fine its context.

E-plore solutions and strategies.

A-ct on the best solution

L-ook back and evaluate the process.

Ensuring Rubrics reliability requires assessing Performance, Product, or Process; in sum must be consistent, valid, reliable. Instructor evaluation of Rubrics can be interrator or intrarater. Interrater check for consistency of scoring by two or more raters. Intrarater check for consistency of scoring by the same rater and different times. Measuring a Rubrics looks for Content, Clarity, Usefulness, Reliability/Validity that include Civic knowledge and engagement, critical thinking, information literacy, inquiry and analysis, intercultural knowledge, reading, teamwork and problem solving, written and oral communication, and many more.

Building and Testing Rubrics requires full understanding of the Criteria and Student requirements.  Rubrics are formatted originally to meet the needs of the learning objective, as used and development evolves and involving others help better define the Rubrics to meet the requirements of learning. Identify the purpose, Identify the Criteria, determine the level of assessment, describe each criterion, involve others in the development, Pre-test and retest rubrics based on feedback.