Tag Archives: ethics

Ethical dilemma of artificial intelligence

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THE ETHICS OF AI: WHAT MAKES 'ETHICAL AI' AND WHAT ARE ITS CHALLENGES?
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One of the popular technological topic dilemmas that I found is the ethical dilemma of artificial intelligence (AI). AI is a technology that can perform tasks that normally require human intelligence, such as reasoning, learning, decision making, and problem solving. AI has many applications and benefits for various fields and sectors, such as health, education, business, and entertainment. However, AI also poses many challenges and risks for society, such as privacy, security, accountability, transparency, and fairness.

How can we guarantee that AI upholds human dignity, rights, and values? One effective approach involves the adoption and implementation of ethical principles and guidelines for AI, as proposed by esteemed entities such as the European Commission, OECD, or the IEEE. These guidelines are crafted to ensure that AI remains human-centric, values-based, and trustworthy, prioritizing the preservation of dignity, rights, and values for both humans and other living beings.

To prevent the misuse of AI for harmful purposes like warfare, cyberattacks, or manipulation, a crucial step is the establishment and enforcement of legal and moral norms and rules for AI. Recommendations from authoritative bodies like the UN, ICRC, or the Partnership on AI can guide efforts to prevent or restrict the deployment of AI in ways that threaten peace, security, or human dignity. Holding accountable those who misuse or abuse AI for such purposes is a key component of this strategy.

Regulating and overseeing the development and use of AI can be accomplished through the creation and support of multi-stakeholder and multi-level governance mechanisms and institutions, as suggested by UNESCO, the Council of Europe, or the Global Partnership on AI. These mechanisms aim to facilitate dialogue, cooperation, and coordination among diverse actors and sectors involved in AI, including governments, civil society, academia, industry, and international organizations. The goal is to ensure responsible and ethical development and usage of AI.

Ensuring inclusivity and diversity in AI, and preventing discrimination or exclusion of certain groups, can be achieved by promoting and protecting diversity and inclusion in AI development. Initiatives advocated by UNDP, the AI Now Institute, or the Algorithmic Justice League focus on designing and deploying AI with the active participation and representation of diverse and marginalized groups, ensuring that AI does not perpetuate existing biases, inequalities, or injustices.

To guarantee that AI is explainable and understandable, fostering trust and control among humans, the development and application of explainable and transparent AI techniques and methods are essential. Approaches recommended by DARPA, FAT/ML, or XAI aim to empower humans to comprehend the logic, reasoning, and outcomes of AI systems. This transparency allows for human oversight and feedback, ensuring alignment with human goals and values.

To prevent the displacement or harm of human jobs, skills, or relationships by AI, enhancing and supporting human capabilities and capacities in AI is crucial. Initiatives proposed by the World Bank, ILO, or WEF strive to ensure that AI serves to augment and complement human skills and abilities, creating new opportunities and benefits for human workers and learners. These efforts emphasize fostering collaboration and connection among humans in the context of AI.

My view on the ethical dilemma of AI is that AI is a powerful and promising technology that can improve the quality and efficiency of human life, but it also requires careful and responsible use and governance. I think that AI should be aligned with human values and interests, and that it should respect the principles of human dignity, autonomy, justice, and solidarity. I also think that AI should be developed and used in a participatory and collaborative manner, involving various stakeholders, such as researchers, developers, users, regulators, and civil society. I think that AI should be subject to ethical standards and legal frameworks that ensure its safety, reliability, and accountability. I also think that AI should be transparent and explainable, and that humans should have the right to know, understand, and challenge the decisions and actions of AI. I think that AI should be beneficial and empowering for humans, and that it should not undermine or threaten human dignity, rights, or well-being. I also think that AI should be compatible and complementary with human skills and abilities, and that it should not replace or harm human jobs, creativity, or social interactions.

Source:
(1) Artificial Intelligence: examples of ethical dilemmas | UNESCO. https://www.unesco.org/en/artificial-intelligence/recommendation-ethics/cases.
(2) Ethical dilemmas in technology | Deloitte Insights. https://www2.deloitte.com/us/en/insights/industry/technology/ethical-dilemmas-in-technology.html.
(3) History of technology – Technological Dilemma, Innovation, Impact. https://www.britannica.com/technology/history-of-technology/The-technological-dilemma.
(4) Top 10 Scientific Technology Challenges in 2021 – Laboratory Equipment. https://www.laboratoryequipment.com/571215-Top-10-Scientific-Technology-Challenges-in-2021/.

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From Farm to Table: How AI is Revolutionizing Food Waste Management

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Source: www.fox16.com

The Enormity of Food Waste: A Global Challenge

Food waste is a massive issue worldwide, impacting both rich and poor countries. Around 35% of the food produced ends up unsold or uneaten, causing significant economic, environmental, and social problems. In the United States, supermarkets are responsible for more than 10% of this surplus food, roughly 10.5 million tons annually. The causes are diverse, from date labels, handling mistakes, and spoilage to overordering due to consumers wanting perfect-looking produce. This leads to not only wasted food but also higher costs and more greenhouse gas emissions when discarded food goes to landfills.

AI-Powered Agriculture: Reducing Farm Food Loss

Farms are using AI to tackle food waste at its source. AI tools, like drones, sensors, and smart farm equipment, provide real-time info on soil health, crop status, and weather. Farmers use this data to make smart decisions on where to grow crops, when to plant, harvest, and rotate crops. AI also helps predict when crops are ready for harvest, reducing the risk of picking them too early. Plus, AI can identify helpful microbes to boost crop growth without synthetic fertilizers. These AI innovations in agriculture could change traditional practices and cut down on food loss before it reaches the market.

AI in Food Management: A Multifaceted Approach

In food management, AI offers a flexible way to fight food waste. Companies like Food Cowboy and Winnow show how AI can make a difference. Food Cowboy’s app connects farmers, food banks, and stores to redistribute surplus food, saving it from being wasted. Winnow’s smart meter in commercial kitchens uses AI to track food waste and suggests changes in portion sizes and menu items. But AI in food management also comes with challenges. It might unintentionally reinforce biases in resource distribution and lead to job losses in the food industry. So, it’s vital to consider ethical data use and involve various stakeholders in creating fair and responsible AI solutions.

Retail Revolution: AI and Predictive Analytics in Food Waste Management

In the retail world, AI and predictive analytics are changing the game in food waste management. By digging deep into sales data and considering various factors like weather, local events, and social trends, AI gives a full picture of consumer demand. It can even predict demand with precision. AI also adjusts prices in real-time, ensuring products close to their expiry date get sold instead of being thrown away. Yet, this shift isn’t without its challenges. It requires retailers to embrace data-driven decisions and move away from old pricing strategies. Plus, AI-driven pricing must find the right balance between profit and reducing food waste. By addressing these challenges and leveraging data’s power, AI is making waves in tackling food waste in the retail sector, aligning with global sustainability and ethical concerns about wasted food.

Sources:

  1. https://www.analyticsvidhya.com/blog/2023/01/food-waste-management-ai-driven-food-waste-technologies/
  2. https://www.techopedia.com/how-ai-can-help-minimize-food-waste-in-commercial-kitchens
  3. https://paccoastcollab.wpenginepowered.com/wp-content/uploads/2022/12/PCFWC-Case-Study_AI_Final.pdf
  4. https://linkretail.com/ai-and-predictive-analytics-pioneering-food-waste-management-solutions-in-retail/
  5. https://www.mckinsey.com/capabilities/sustainability/our-insights/sustainability-blog/how-ai-can-unlock-a-127b-opportunity-by-reducing-food-waste
  6. Chat GPT – https://chat.openai.com/share/41cdb22d-f925-4469-9407-110ae2acf7f4
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What’s Responsible AI – An alternative guideline

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EU Ethics Guidelines for Trustworthy AI

© inserted from twitter, Original image from EU Ethics Guidelines for Trustworthy AI

Artificial intelligence is one of the fastest growing fields today. It is currently being used in several disciplines, across the globe. However, this technology needs to be monitored to prevent any bias or negative impacts from affecting the world.

Responsible AI is developed to help prevent any harmful implications of AI, by having policies related to bias, ethics and trust. It is relatively new; however, many companies are favoring its incorporation into their infrastructure.  Responsible AI caters to managing and regulating intelligent systems, to make sure they do not harm the society.

There are three major contributors to consider while determining if a certain piece of AI tech is suited for the society:

  • Awareness

Awareness of the accountability of AI research and development is necessary. That is, who is to blame if an intelligent machine makes an error? The research should be capable of determining the possible effects of releasing a system into the world.

  • Reason

AI algorithms learn from the data they receive. However, they should be capable of reasoning and justifying their actions.

  • Transparency

Transparency is required to make sure people know what a particular intelligent system does, and what it is capable of. It requires governance to ensure it delivers societal good.

responsible-ai-toolkit

© Image Inserted from pwc.com

Responsible AI research is being done across different platforms to devise rules and regulations to govern AI. RRI (Responsible AI Research and Innovation) is an interactive and transparent process that holds individual or groups of innovators responsible for the acceptability, desirability and sustainability of a certain technology in the society. It can be implemented between different parties using the following approaches:

  1. Permanent individuals/groups from different backgrounds can discuss the innovation and its possible outcomes. This includes ethical review boards within organizations.
  2. Set of rules and guidelines that should be followed by the outcomes of research and innovation, so its ethical, legal and safe.
  3. Code of conduct detailing on the behavioral choices for stakeholders in different sectors
  4. Industry standards that set a minimum threshold for the safety required for testing and development of new technology.
  5. Approaches and methods of keeping track of the future impacts of a particular technology like scenario planning and modeling.

Since AI is prone to biases and misjudgments, RRI can ensure the technology is being utilized for the ultimate good of the world. At the end, human input is required to make sure technology is not going against humanity and that the processes are following the ethics, trust and bias standards. This improves accountability and promotes a better public image of such systems.

 

 

Resources:

Wikipedia

ngi.eu

Tandfonline

Google Responsible AI

ec.europa.eu

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