Gary Ackerman @garyackerman@qoto.org

Ultimately, the curriculum of the future is a result of actively engineering minds & mentalities to enact a preferred vision of society. It's shaped by complex interactions of economy, culture, expertise, & identity.

Learning is increasingly positioned as a lifelong, lifewide activity, harmonized across formal & informal spaces. It's becoming a lifestyle choice, often commodified, where consuming equals learning. #LifelongLearning #ConsumerCulture

Societies are increasingly understood through a "cybernetic style of thought" – saturated with metaphors like networks, flexibility, speed, virtuality. This style shapes how the curriculum is remade. #Cybernetics #EdTech

Curriculum is like a "saddleback," looking both to the past & promoting a vision for the future, expressing legacy, aspirations, & anxieties. It's far from neutral or nonpolitical. #CurriculumDesign #EducationPolicy

Humanizing pedagogies have historical roots in Paulo Freire's work, emphasizing critical consciousness, power, privilege, and ideology, not just methods.

The AI control problem is paramount: ensuring future advanced AI remains beneficial and aligned with human values, avoiding potential existential risks. #AIControl #ExistentialRisk

In accident scenarios, potential AI ethical programming includes Retributivist (harm responsible party), Selfish (protect AI's occupant), and Utilitarian (minimize overall harm). Each has implications. #AIethics #DecisionMaking

The concept of AI personhood is highly debated. Should AI systems have rights or responsibilities similar to humans or corporations?

The propagation of misinformation online, sometimes amplified by AI, is a serious issue impacting politics and societal trust. #Disinformation #AI

Companies leverage user-generated data to improve services and user experience, but this practice has led to concerns and regulations like GDPR. #DataPrivacy #UserData

As automation progresses, workers will likely need to acquire new skills to remain competitive. This shift could widen the gap in income inequality. #Upskilling #Workforce

Beyond just job displacement, the increasing capabilities of AI, especially in mimicking human intelligence, raise complex ethical questions.

AI has the potential to increase productivity, but its impact on economic inequality is a significant concern.

Asimov's Three Laws of Robotics outline foundational rules for robots: no harm to humans, obey human orders (unless conflicting with rule 1), and protect self (unless conflicting with rules 1 or 2).

Learning Analytics can operate at four levels: Descriptive (what happened?), Diagnostic (why?), Predictive (what will happen?), and Prescriptive (what action to take?). Each level builds upon the last.

#AI is reshaping education and the fundamental relationship between technology & humans. It's considered essential for the education ecosystem, preparing future generations. #EdTech #ArtificialIntelligence

Empirical support for ICAP shows that I>C>A>P learning effectiveness is consistent with pair-wise predictions. Many studies support the idea that Interactive, Constructive, & Active are better than Passive.

Extraneous Cognitive Load is imposed by instructional procedures that unnecessarily increase element interactivity. Good instruction aims to reduce this.

Biologically secondary knowledge, like reading or most school subjects, requires explicit instruction and conscious learning because we haven't evolved to acquire it automatically.

Biologically primary knowledge, like learning to speak, is acquired automatically, without explicit tuition or conscious effort. #PrimaryKnowledge #AutomaticLearning