Elon Musk once stated, "With Artificial Intelligence , we are summoning the demons. This quote highlights the surge impact of AI and machine learning in our everyday life that can be startling too. Though, there is no suspicion in the fact that AI and machine learning are the name of efficiency andRead more
Elon Musk once stated, “With Artificial Intelligence , we are summoning the demons.
This quote highlights the surge impact of AI and machine learning in our everyday life that can be startling too. Though, there is no suspicion in the fact that AI and machine learning are the name of efficiency and sophistication but on the other hand, have some swindling effect too. The below stated pointers are some of the ethical implications of AI and Machine Learning in everyday life:
PRIVACY AND SECURITY:
AI Algorithms are used to process data and this data may also contain personal information of the individuals that can be used fraudulently. However , the user who has designed the algorithms should be responsible for the decision making of the AI.
BIAS ALGORITHM:
The places where AI is implemented like libraries, stores or the places where recruitment is taken place , have become a source of bias algorithm. Partisanship takes place based on the personal information of the individuals that may include discrimination on the basis of color, caste , creed ,gender among them .This leads to the selection in a total unfair means.
INCREASING UNEMPLOYMENT RATE:
AI generated tools are playing a vital role in the displacement of jobs of people. The human based tasks like content writing , making presentations and research on any topic and many more , are indubitably completed by AI algorithms and machine learning.
THREATENING TO HUMAN EXISTENCE:
One of the most alarming implications of AI and machine learning is that they could easily be used to harm human existence. As these machines possess human intelligence, they can easily be programmed to be self aware and to contemplate humans as a threat to them. In this way, these machines can be used for the purpose of wars or terrorism .
CONCLUSION:
The user who implements and processes the algorithms should be responsible for the safety of the consequences and should make sure that the system is working for the betterment of the society. In this way, the flustering upshots of AI and machine learning implementation can be eradicated.
Benefits of Migrating Enterprise Applications to the Cloud: Cost Savings Reduced Costs on IT Infrastructure: They do not directly invest in comericial equipment and services such as on-site hardware (servers, storage, networking equipment) and data centers and their cooling systems Pay-as-You-Go ModRead more
Benefits of Migrating Enterprise Applications to the Cloud:
Cost Savings
Reduced Costs on IT Infrastructure: They do not directly invest in comericial equipment and services such as on-site hardware (servers, storage, networking equipment) and data centers and their cooling systems
Pay-as-You-Go Model: Most cloud providers align this cost on the actual usage to enable the up or down scaling on cost outlay.
-Rapid scaling: Optional users may be increased or decreased instantly in response to a range of rarely occurring or unpredictable high levels of demand, for example at the end of calendar years, academic years or fiscal years. Faster time to market: The fast deployment of applications and services ensures that new products/services are developed and launched on the market faster.
Higher Innovation
-Access to Cutting-Edge Technologies: Get more access to the cloud services, such as AI/ML, big data and IoT, to transform business models for growth.
-Focus on Core Business: Divert IT infrastructure responsibilities and workload leaving room for IT to deliver more on strategic concerns that supports the business.
Improved Security:
-Strong Security: Cloud providers invest a lot of money in security and its deployment and follow the best practices to shield data and applications from threats.
Difficulties in Migrating Enterprise Applications to the Cloud:
Security:
Data Breaches: The cloud providers may offer strong protection measures but there are still data leaks.
Compliance Issues: Implementing privacy rules for data storage sharing particularly in the current increased cloud utilize (for example the GDPR or CCPA ).
Vendor Lock-in:
Dependence on the Cloud Provider: Data and applications are moved to a specific cloud provider and this make it complex to do the same with another in future hence creating vendor lock in.
Integration Challenges:
Integration with Existing Systems: However, they also posed some important challenges that include the following: The integration of the cloud-based applications with the existing on site systems and applications is always a challenge.
Cost Management:
Unexpected Costs: The following costs are also possible if not checked frequently; data transfer charges, storage fees, and the emergence of surge in usage among others.
Data Migration:
Data Quantity: Heavy volume data migrating into the cloud will be complex and time-consuming potentially causing disruption to daily business routines.
Skilling Gap:
See less-Cloud Savvy: For successful handling and management of applications powered through cloud, organizations must build their skills.