; (B) minimization of inappropriate bias in training data sets or algorithmic feature selection; (C) qualitative and quantitative forecasting of future capabilities and applications; and (D) the societal and ethical implications of artificial intelligence; (2) use existing authorities and programs and collaborate with other Federal agencies— (A) to improve the teaching and learning of artificial intelligence science and engineering during the primary, secondary, undergraduate, graduate, postgraduate, adult learning, and career retraining stages of education; (B) to increase participation in the artificial intelligence fields, including by individuals identified in sections 33 and 34 of the Science and Engineering Equal Opportunities Act ( 42 U.S.C. 1885a ; 42 U.S.C. 1885b ); (C) to formulate goals for education activities related to artificial intelligence engineering and research to be supported by the National Science Foundation related to topics important to the Initiative, including— (i) algorithm accountability; (ii) algorithm explainability; (iii) consumer data privacy; (iv) the assessment and minimization of inappropriate bias in training data and output; (v) the societal and ethical implications of the use of artificial intelligence; (vi) algorithm trustworthiness; and (vii) algorithmic forecasting; (D) to engage with institutions of higher education, research communities, potential users of information produced under this section, entities in the private sector, and non-Federal entities— (i) to leverage the collective body of knowledge from existing artificial intelligence and engineering research and education activities; and (ii) to support partnerships among institutions of higher education and industry that facilitate collaborative research, personnel exchanges, and workforce development; (E) to coordinate research efforts funded through existing programs across the directorates of the National Science Foundation