Some of the ethical issues that arise from the development of AGI include concerns over its impact on employment, its potential to make decisions that may harm humans, and the question of who should be responsible for its actions.

The 'control problem' refers to the challenge of ensuring that advanced AI systems act in accordance with human values and goals, even as they become more intelligent and autonomous.

Some proposed solutions to the control problem include designing AI systems with intrinsic motivations that align with human values, developing 'friendly' or 'aligned' AI that is explicitly programmed to act in accordance with human values, and establishing frameworks for AI governance and oversight.

Cognitive computing is a type of AI that seeks to emulate the way humans process information, using natural language processing, machine learning, and other techniques to understand and interpret data.

Language is a critical component of AI, as it enables machines to communicate with humans and process unstructured data. Natural language processing and generation are areas of active research in AI.

The Turing Award is often referred to as the 'Nobel Prize of Computing' and is awarded annually by the Association for Computing Machinery (ACM) to individuals who have made significant contributions to the field of computer science and AI.

Some current trends and developments in AI research include the development of explainable AI, the use of deep learning to improve perception and decision-making, and the exploration of bio-inspired approaches to AI, such as neural networks and evolutionary algorithms.

Quantitative research involves measuring numerical data and analyzing it statistically, while qualitative research involves in-depth exploration of non-numerical data.

Experimental research allows researchers to establish a cause-and-effect relationship between variables, and it provides a high level of control over extraneous variables.

Experimental research can be expensive and time-consuming, it may not generalize well to real-world situations, and ethical concerns can arise when manipulating variables.

A correlational study investigates the relationship between two variables without manipulation of either variable.

A longitudinal study follows a group of participants over time, allowing researchers to see changes and development over time.

A cross-sectional study compares different groups of participants at a single point in time, allowing researchers to see differences across groups.

A case study is an in-depth examination of a single individual or group, often used to investigate atypical cases or rare phenomena.

A naturalistic observation involves observing participants in their natural environment without manipulation of variables.

The placebo effect is the phenomenon where a participant's beliefs or expectations about a treatment can lead to positive or negative effects, even when the treatment itself is non-active.

Measurement validity refers to the degree to which a measurement accurately reflects the construct it is intended to measure.

Reliability refers to the consistency and stability of a measurement over time and across different situations.

Random sampling involves selecting participants for a study at random, ensuring that everyone in the population has an equal chance of being included in the sample.

A stratified sample involves dividing the population into subgroups and then selecting participants from each subgroup in proportion to their representation in the population.