Tag Archives: AI

Americans’ attitudes about artificial intelligence (AI)

Sharing information from a Pew Research Center survey on Americans’ attitudes about artificial intelligence (AI).

Pew Research Center surveyed 11,201 U.S. adults between July 31 and August 6, 2023.

The survey found that a growing number of Americans are expressing concern about the role AI plays in daily life. Specifically, 52% of Americans feel more concerned than excited about the increased use of AI, while only 10% are more excited than concerned, and 36% feel an equal mix of both emotions.

The survey also revealed that concern about AI outweighs excitement across all major demographic groups, though there are some differences by age. Older adults, aged 65 and older, are mostly concerned (61%) about the growing use of AI.  Younger adults, aged 18 to 29, also showed concern; concerned (42%) and excitement (17%).

The rise in concern about AI aligns with a rise in public awareness. Nine out of ten adults have heard at least a little about AI, with a 7-point increase in the share who have heard a lot about AI since December 2022. Those who are more aware of AI are 16 points more likely to express greater concern than excitement about it. Those who have heard a little about AI are also 19 points more likely to express concern compared to December 2022.

Despite the overall concern, opinions about AI’s impact in specific areas are more mixed. For example, 49% of Americans believe that AI helps more than hurts when it comes to finding products and services online. However, when it comes to privacy, 53% of Americans believe that AI does more to hurt than help in keeping personal information private.

The survey also found notable demographic differences. Americans with higher levels of education tend to view AI’s impact more positively across various use cases. Men also tend to view AI’s impact more positively than women. However, when it comes to privacy, both college graduates and adults with lower levels of education expressed concern about AI’s negative impact.

It’s important to note that these attitudes and opinions are still developing as AI continues to advance and be integrated into various aspects of daily life.


Computer Education

Global spending on Artificial Intelligence (AI) is expected to reach $35.8 billion this year. That’s up 44% from last year. It’s expected to double to over $79.2 billion by 2022.

Below are some terms that will help you to better understand this exploding and learned  technology.

Natural Language Processing (NLP) –A subfield of computer science, information engineering, and AI focused on interactions between computers and human language.  When text or speech is input and it can be read or extract meaning.

Artificial Intelligence (AI)- Sometimes called machine intelligence, AI is intelligence demonstrated by machines. These machines mimic “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

Deep Learning -Sometimes referred to as deep structured learning or hierarchical learning, it is part of a broader family of machine learning methods based on artificial neural networks.

This powerful statistical technique is used for classifying patterns using large data sets and ANNs (Artificial Neural Networks). Deep learning neural networks have been applied to fields including natural language processing, social network filtering, drug design, medical image analysis, and game programs. They have produced results comparable to and in some cases superior to human experts.

Machine learning (ML) -The scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.



AI IS Listening

Artificial Intelligence (AI) is able to measure tone, tempo and other voice characteristics. Some systems compare those sounds to stored speech pattern libraries that define a plethora of human emotions to determine an individual’s emotional, mental or even physical health.

When this sound technology is used in conjunction with computer vision, the science that allows computers to gain a high-level understanding from digital images or videos, the  applications become even more powerful. For example, imagine a vehicle that is able to hear a driver yawning and see the driving dozing off.

Research firm Gartner Inc predicts that within three years, 10% of personal devices will have emotion AI capabilities that include wearables (similar to a Fit Bit) that is able to monitor an individual’s mental health or video games that adapt to the players mood.