SOME NAME ☰
Computing innovation has been an ongoing progression in the twenty-first century. Progressions in areas such as artificial intelligence can have beneficial effects but can also be harmful. An example of this is ChatGPT. Though it can help with quick research, it gives students an easy way to cheat on their homework assignments and research projects. Computing innovation has its upsides but with every positive there will always be a negative. Computing innovation often will have an impact beyond its intended purpose. While working to find a solution to one problem, computing can often find itself leading to advances in another field of work. Machine learning is an example of having an impact beyond its intended purpose. Through machine learning we have learned valuable things in areas such as science, which in turn can help make new breakthroughs in medicine. Technology has been rapidly evolving in the past few decades and through computing innovation it is shown to have benefits previously not intended to happen. With the advancement of computing innovation the way we approach our day to day lives gets further impacted with technology. Improvements in the way we communicate and learn have all stemmed from computing innovation. An example of this is the way we study the human body. With the help of computing, scans such as X-rays have vastly improved in their quality, especially with the help of AI. Artificial intelligence can identify diseases in X-ray scans as accurately or even better than a human can which can play an impactful role in fighting off diseases early. Though there are benefits to computing innovation, it can also cause harm. Technology has become so advanced in the past decade, almost to the point where it can soon replace peoples' jobs. With the rise of artificial intelligence, there is a lesser need for people in industries such as retail service. As artificial intelligence gets more and more advanced there will be a high likelihood of cashiers being replaced by AI. As seen with projects such as Amazon Go where there is no cashier and AI recognizes what items you take and automatically charges the person for those items. What is the digital divide? Digital divide is the gap between people who have access to technology and those who don’t. The ability to access technology is based around demographic, geographic, and socioeconomic factors. An example of this is how in households with income under $30,000, 29% don’t own a smartphone. This contributes to the gap between people with and without technology. Some contributing factors to the digital divide are different age demographics and less technologically advanced areas of the world. Older generations are unable to keep up with today's day and age. With many things going digital such as doctor’s appointments many people may struggle because they lack the technological skills to do so. To close the digital divide locally, affordable internet services for homes along with additional courses to enable less advanced people into the world of technology. On a global scale initiatives to give third world countries and other areas where there is a large divide courses and training with day to day technology will be necessary to improve upon the digital divide.
What is computer bias? Computer bias is when computers unfairly discriminate against certain groups of people in favor of another. An example of computer bias is in Amazon’s recruiting engine. This engine is artificial intelligence that analyzes resumes of job applicants to see which ones will be called in for an interview. The algorithm was pointed out to be biased against women in the recruitment process. This is an example of computer bias as it discriminates against a group of people, in this case being women. Computer bias can also result from biases in the data used to train machine learning algorithms. An algorithm can inherit and reinforce biases in its decision-making if the data used to train it is prejudiced, such as if it contains discriminating patterns or reflects societal preconceptions. Certain groups of people may experience unjust outcomes as a result of this. The algorithm used by Amazon's hiring tool was trained using resumes that were submitted to the business over a ten-year period and were largely made up of male candidates. As a result, the algorithm was unfair to female candidates and prejudiced in favor of male applicants, demonstrating how biased data can unintentionally induce bias into computer systems. Data and algorithms must be addressed in order to eliminate computer bias. Curate and preprocess data first to reduce biases. Second, create algorithms and assess them while keeping an eye out for any biases that might exist. Utilize fairness-conscious machine learning and routine audits. Participate in development, testing, and deployment with a variety of teams. Get opinions from the affected communities. Computer prejudice can be reduced and fairness in artificial intelligence systems can be fostered by adopting a proactive and comprehensive strategy. Crowdsoucing is the practice of obtaining information or input into a task or project by enlisting the services of a large number of people, either paid or unpaid, typically via the internet. By crowdsourcing companies are able to save time and money by hiring someone else to do work for them. This can allow companies to bring in new people with different skill sets to a business. Crowdsourcing can also be more efficient compared to traditional methods of problem-solving or idea generation. Traditional approaches often rely on a limited number of individuals or small teams, which may be constrained by time, expertise, or biases. In contrast, crowdsourcing enables a larger number of individuals to contribute, resulting in a wider variety of ideas and perspectives. This can lead to faster and more comprehensive results as businesses can leverage the collective intelligence of the crowd to identify and solve problems, generate ideas, or complete tasks more efficiently. Furthermore, crowdsourcing can benefit from the wisdom of crowds, where diverse opinions and perspectives can collectively lead to better decision-making. By tapping into a diverse crowd, businesses can avoid biases that may be present in a small group or an individual's decision-making process. The collective intelligence of the crowd can lead to more accurate and informed decisions, and businesses can gain insights and ideas that may not have been possible through traditional methods. In summary, crowdsourcing offers businesses the opportunity to access a diverse talent pool, generate innovative solutions, and make more efficient decisions. It harnesses the collective intelligence and creativity of a crowd, providing businesses with valuable insights, ideas, and cost-effective solutions to their challenges.
With the increased rise of technology there are bound to be some programs that overlap each other in some way. This can raise many legal and ethical issues into the world of computing. Some legal and ethical issues can be the copying of programs or the breach of privacy we face everyday using the internet. Crime such as identity theft have become more prevalent with the rise of technology. This is a legal issue because someone is hacking onto a personal computer and taking legal documents such as birth certificates. Another legal and ethical issue is bias and discrimination in computing systems. Bias can be inadvertently introduced into algorithms and models used in computing applications, leading to discriminatory outcomes. This can have serious societal implications, such as perpetuating existing social inequalities and reinforcing bias against certain groups of people, such as minorities or marginalized communities. Legal and ethical questions arise in addressing issues of algorithmic fairness, accountability, and transparency in computing systems to prevent discrimination and ensure fairness in the use of technology. In education, computing has also raised legal and ethical concerns. Issues such as data privacy and security are relevant in educational settings, as schools and educational institutions collect and store sensitive student data. There are also concerns about the ethical implications of using data-driven technologies in educational decision-making, such as student evaluations of performance assessments, as it may raise questions about fairness, transparency, and accountability. Additionally, there are ethical concerns related to the use of artificial intelligence in education, such as bias in automated grading systems or the ethical implications of using AI for surveillance or monitoring of students' behavior. In conclusion, computing technologies raise legal and ethical issues that impact society and education in various ways. Privacy, data protection, algorithmic fairness, and ethical use of technology are among the key concerns that require robust legal and ethical frameworks to ensure responsible and ethical use of computing in society and education. It is important for stakeholders, including policymakers, educators, and technology developers, to actively engage in addressing these legal and ethical challenges to ensure that computing technologies are used in a responsible and ethical manner for the betterment of society and education. Safe computing is keeping your personal data secure with the use of security measures. By using secure passwords and browsing on secure websites you are able to keep your data safe. This can help prevent things like identity theft from hackers attempting to enter your computer. This can help keep you safe as well as the people around you. Safe computing is crucial for society at large as technology is pervasive in various aspects of our daily lives, including communication, commerce, healthcare, transportation, and government services. Cybersecurity breaches can result in financial losses, identity theft, and other forms of harm to individuals and organizations. Cyber attacks on critical infrastructure, such as power grids or transportation systems, can have far-reaching consequences and impact the safety and well-being of society. Therefore, implementing strong cybersecurity measures is essential to protect individuals, businesses, and critical infrastructure, and to maintain the trust and integrity of technology in society. Protecting against external threats, safe computing also involves promoting responsible use of technology within schools and society. This includes educating students, teachers, and other users about safe online behavior, such as avoiding sharing personal information with strangers, being cautious of phishing emails or suspicious links, and using strong and unique passwords. It also involves promoting ethical use of technology, including respecting copyright laws, avoiding plagiarism, and being mindful of the social and emotional impact of technology on mental health and well-being. By fostering a culture of safe and responsible computing, schools and society can mitigate risks and promote positive and secure technology use practices. In conclusion, safe computing is crucial in schools and society to protect against cybersecurity threats, safeguard sensitive data, and promote responsible technology use. It involves implementing robust cybersecurity measures, educating users about safe online behavior, and promoting ethical use of technology. By prioritizing safe computing practices, schools and society can ensure the secure and responsible use of technology for the benefit of individuals, organizations, and society as a whole.
×